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Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-05-31.

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Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-05-31.
Physical Description: Book
Language: english
Creator: Zambrana, Katheryn Gabrielle
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

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Subjects / Keywords: Sociology and Criminology & Law -- Dissertations, Academic -- UF
Genre: Criminology, Law, and Society thesis, M.A.
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theses   ( marcgt )
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Electronic Thesis or Dissertation

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Statement of Responsibility: by Katheryn Gabrielle Zambrana.
Thesis: Thesis (M.A.)--University of Florida, 2012.
Local: Adviser: Lane, Jodi S.
Electronic Access: INACCESSIBLE UNTIL 2014-05-31

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Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044156:00001

Permanent Link: http://ufdc.ufl.edu/UFE0044156/00001

Material Information

Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2014-05-31.
Physical Description: Book
Language: english
Creator: Zambrana, Katheryn Gabrielle
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: Sociology and Criminology & Law -- Dissertations, Academic -- UF
Genre: Criminology, Law, and Society thesis, M.A.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Statement of Responsibility: by Katheryn Gabrielle Zambrana.
Thesis: Thesis (M.A.)--University of Florida, 2012.
Local: Adviser: Lane, Jodi S.
Electronic Access: INACCESSIBLE UNTIL 2014-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0044156:00001


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CRIME & DELINQUENCY / OCTOBER 2000 Lane, Meeker / SUBCULTURAL DIVERSITYSubcultural Diversity and the Fear of Crime and GangsJodi Lane James W. MeekerFearandgangsweretwoofthemostimportantfactorsdrivingcrimepolicyinthe1990s. Policymakersandthemediablamedgangsformuchoftheviolenceoccurringacrossthe nationandforpublicfear.ThisarticleexaminesfearofcrimeandgangsinOrange County,California,asmeasuredbyarandomizedsurveyof1,223respondentscon ductedin1995by TheOrangeCountyRegister newspaper.Theauthorsfindthatthefac torspredictingfearofcrimeandfearofgangsaredifferent.Inaddition,theyfindthat concern about subcultural diversity is a strong predictor of both types of fear.Thepublic’sfearofcrimeandgangsbecameoneofthestrongestmotivatingforcesbehindlegislators’callsforharsherpoliciestowardcriminals duringthe1990s(see JuvenileCrime:BreakingtheCycleofViolence ,1994). Gangmembersbecamethestereotypicalcriminalsofthedecade,being blamedforrandomviolentcrimesagainstinnocentcitizens.Forexample,in 1994,thenDeputyAssistantDirectoroftheFederalBureauofInvestigation (FBI)JamesC.FriersaidatahearingbeforetheU.S.Congress,“Innearly everymetropolitanareaofthiscountry,streetgangsareresponsibleforasubstantialportionoftheincreaseinthecrimesofviolence”( Thegangproblem inAmerica ,1994,p.14).Promptedinpartbyacademicandpractitioner warningsofincreasinggangproblems,PresidentClintondeclareda“waron gangs”in1997(Clinton,1997),andthenationalOfficeofJuvenileJustice andDelinquencyPrevention(OJJDP)heldtwoNationalYouthGangConfer ences(in1996and1999).AsBest(1999,p.2)recentlynoted,“concernabout random,senselessviolencehasbecomeacentralthemeofcontemporary culture.”497 JODILANE :AssistantProfessorofSociology,CenterforStudiesinCriminologyandLaw, UniversityofFlorida. JAMESW.MEEKER :Professor,DepartmentofCriminology,Law& Society, School of Social Ecology, University of California, Irvine. TheauthorswouldliketothankBobOlintoof TheOrangeCountyRegister forprovidingthe surveydataforthisanalysisandKarenF.Parkerandthreeanonymousreviewersfortheirinsight fulcommentsonanearlierdraft.Apreliminaryversionofthisarticlewaspresentedatthe November 1996 American Society of Criminology Meetings in Chicago.CRIME & DELINQUENCY, Vol. 46 No. 4, October 2000497-521 2000 Sage Publications, Inc.

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Althoughthemediaandpolicymakersoftenfocusonthepublic’sgeneral fearofcrime,recentresearchindicatesthatfearofcrimeiscomplexandthat peoplefeardifferentcrimesdifferently(Ferraro,1995;Rountree,1998; Rountree&Land,1996;Warr,1994).Forexample,peoplemightfeardrivebyshootingsorhome-invasionrobberiesmorethanburglarybecausetheper sonal harm is potentially greater for violent crimes than for other crimes. Anotherfocusofrecentfear-of-crimeresearchisoneffortstoexplainwhy thosepersonswiththegreatestriskofcriminalvictimization(e.g.,young males)arenotthemostfearful(seeWarr,1994).Focusingonthecommunity dynamicsthatpredictfearofcrime,onetheoreticalapproachcontributingto ourunderstandingofwhypeoplewhomaynothavethehighestobjectiverisk ofvictimizationareafraidissubculturaldiversity(Merry,1981).Thistheory, groundedinthesocialdisorganizationtradition,positsthatconcernabout racialandethnicdiversityandmisunderstandingsaboutculturaldifferences arethecriticalfactorsexplaininggreaterfearofcrimeinthosewhoarenot necessarilyathigherriskforbeingvictimized(Covington&Taylor,1991; Merry,1981).Examiningthistheoryseemsanimportantundertaking,given themediaandpoliticalfocusonracialandethnicminoritiesastheperpetratorsofcrime(e.g.,WillieHorton)andasmembersofgangs(seeBaer& Chambliss,1997;Best,1999;Irwin,Austin,&Baird,1998;Madriz,1997; Sacco, 1998). Previousresearchhasnotaddressedthedifferencesbetweenfearofcrime generallyandspecificsourcesoffearofcrime,suchasgangs.Moreover,there havebeenfewstudiesthatexaminetheeffectsofconcernaboutsubcultural diversityonfearofcrime(butseeChiricos,Hogan,&Gertz,1997;Co vington& Taylor,1991).Thisarticlebuildsonthefear-of-crimeliteratureinthreeways. First,weexaminethegeneralfearofcrimeandthespecificfearofgangssep aratelytoallowdifferencestoemergeinthepredictivefactorsforeachkind offear.Second,welookatthedifferentialimpactofconcernaboutdiversity onfearofcrimeversusfearofgangsaftercontrollingfordemographicfac tors.Third,westudytheindirecteffectsofdemographicsthroughconcern aboutsubculturaldiversityonfearofcrimeandfearofgangstoallowrela tionships to emerge that are not evident in a noncausal model analysis. POLITICAL CONTEXT Inrecentyears,gangshavebeentargetedformuchofthefearandviolence thatexistinurbancommunities.Themediaoftenanchorcrimestoriesbynot ingwhethertheyaregangrelatedandblamegangsforharmingcommunities (Lane,1998).Politiciansroutinelycitecitizenfearwhenintroducingand498CRIME & DELINQUENCY / OCTOBER 2000

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advocatingneworharshercrimepoliciesandoftenarguethatmuchofthe behaviorthepublicfearsisadirectresultofcriminalgangs.AstheCalifornia CouncilonCriminalJustice(1995,p.7)noted,“Nomatterwhereonelives, thefearofviolentjuvenilecrimehasbecomeoverwhelming.”Inthisvein, PresidentClintonmade“fightinggangs”atoppriorityofhissecondadminis trationandunveiledproposalstofightjuvenileviolenceandgangcrime (Peterson,1997).Inhis1997StateoftheUnionAddress,PresidentClinton calledfora“warongangs”andindicatedthattobuildstrongercommuni tieswe“shouldstartwithsafestreets”(Clinton,1997).Moreover,Senator DianeFeinsteincoauthoredandintroducedaSenatebilltermedTheFed eralGangViolenceActof1997afterbeingpromptedbythemurderof 3-year-oldStephanieKuhenonanEastLosAngelesstreet,acasethat sparkednationwidepresscoverageandwidespreadconcernaboutgangs.She notedthatthiseffortrecognized“thegrowingproblemofgangviolenceas oneofthemostimportantissuesfacingournation’stownsandcities” (Feinstein, 1997, p. 1). CaliforniaandSouthernCalifornia,inparticular,havebeenconcerned aboutrisingnumbersofgangmembers.Popularwisdomholds(andgang researchshows)LosAngelesasoneofthemajorgangcapitalsintheUnited States(Klein,1995;Maxson,1999).Policetherehavebeenstrugglingwith gangcrimeforyears.Recentrevelationsaboutthecorruptionandbrutality committedbymembersoftheLosAngelesPoliceDepartmentRampart DivisionCRASHUnitindicatethatsomepolicehavebeenwillingtoresortto illegalactivitiesintheireffortsto“eradicate”gangactivityandputgang membersinprison(Lait&Glover,2000).Duringthe1980sand1990s,Californiapassedmanylawsdesignedtohelppoliceandcommunitiescombat crimebystreetgangs.Forexample,thelegislaturepassedbillsdesignedto battledrugs,drive-byshootings,andwitnessintimidationduringthe1980s (seeJackson,1993).OneofthetoughestlawswastheCaliforniaStreetTer rorismEnforcementandPreventionAct(STEP),whichwaspassedin1988. Sincethatdate,thislawhasgivenpoliceandprosecutorsmorepowerto arrest,prosecute,andpunish“criminalstreetgangs.”Instatingtheneedfor suchacomprehensivelaw,thelegislaturenotedintheactitself:“TheStateof Californiaisinastateofcrisiswhichhasbeencausedbyviolentstreetgangs whosemembersthreaten,terrorize,andcommitamultitudeofcrimesagainst thepeacefulcitizensoftheirneighborhoods”(STEPActof1988,p.67).In 1996,Californiansalsooverwhelminglyapprovedpropositionsthatcreated sentencingenhancementsforthegang-relatedcrimesofcarjackingand drive-by shootings (“How California Voted,” 1996). LocallawenforcementleadersinOrangeCounty,thesouthernneighbor ofLosAngelesCounty,becameincreasinglyconcernedaboutthe“comingLane, Meeker / SUBCULTURAL DIVERSITY499

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storm”ofgangactivityduringthe1990sand,in1992,createdtheCountyWideGangStrategySteeringCommittee(GSSC).Thiscommitteesetoutto createanintensive,hard-hittingstrategytocombatlocalgangcrimethrough lawenforcementsuppressioneffortsandthrougheducatingthepublicabout gangs and gang crime. Their mission wastodevisemethodsforimprovingthequalityoflifeinOrangeCountybyreduc inggangviolenceandillegaldrugusethrougheducation,enforcement,and communitysupport.(OrangeCountyChiefs’andSheriff’sAssociation [OCCSA], 1997, p. 5)Since1992,GSSCsuppressionstrategieshavecenteredonTri-Agency ResourceGangEnforcementTeams(TARGET)—acooperativeeffortbe tweenthepolice,thedistrictattorney,andprobationtoidentify,arrest,and fullyprosecute“targeted”gangsandgangmembers.Tobetterunderstand theireffectsongangcrimetrends,theGSSCcreatedacooperativedatabase calledtheGangIncidentTrackingSystem(GITS)totrackgangincidentson acountywidebasis(seeVila&Meeker,1997).Theseleadersalsosetoutto educatethepublicaboutgangsandgangcrimethroughaneducationand awarenessprogramcalledProject:NoGangsandthroughpressconferences todisseminateinformationaboutgangcrimeascollectedthroughGITS(see OCCSA, 1998). Locallawenforcementandmediaactivitypriortothesurveyusedhereis animportantcontexttounderstandingitsfindings.Beforelate1995whenthe dataforthisstudywerecollected,lawenforcementandotherlocalpolicy makersreportedtotheOrangeCountypublicincreasesinthenumberof gangsandgangmembersandincreasesinthenumberofgang-relatedmur ders.BetweenJanuary1991andtheendof1995,thereportednumberof gangsandtaggercrewsincreasedfrom192to341,andthereportednumber ofidentifiedgangmembersincreasedfromapproximately12,000to21,328. AccordingtoareportbytheOrangeCountyDistrictAttorney,thenumberof solvedandunsolvedgang-relatedmurdersincreasedfrom31occurringin 1991to70in1995(Capizzi,1996).Inaddition,intheyearsprecedingthis survey,thereweresomehigh-profilegang-relatedincidentsthatwerewidely reportedbythelocalmediaasevidencethatthecountywas“notimmune” fromgangviolence(Saavedra,1992,p.B6).Twocasesreceivedconsiderable mediaandpolicy-makerattention.First,in1991,ateacher’saidewasshot andkilledbygangmembersonthewayhomefromthegrocerystore(Horton, 1991),andin1993,ateenagerwaskilledbygangmembersinanaffluentarea ofthecountynotassociatedwithgangactivity(Saavedra,1992).1Thepublic wasbeinginformedbydifferentagenciesinthecriminaljusticesystemand500CRIME & DELINQUENCY / OCTOBER 2000

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bythemediathatgangsandgangviolenceweregrowingproblemsjustprior to the newspaper survey that is the subject of this analysis. IMPORTANCE OF SEPARATING GENERAL FEAR OF CRIME FROM SPECIFIC FEAR OF GANGS Thewidespreadpoliticalandcriminaljusticeconcernaboutgangsleads onetoaskwhetherthegeneralpublicisasconcernedaboutgangsaspolicy makerswouldleadustoconclude.Gang-relatedfearofcrimeisanimportant issuenotonlyforpolicypurposesbutalsoforempiricalandtheoretical ones.Althoughresearchershavenotedthatfearislikelytobecrimespe cific,moststudieshavenotexaminedfearofparticularcrimes(Ferraro,1995; Rountree&Land,1996;Warr,1994).Measuresoffearofcrimeareoften broad(i.e.,thestandardGeneralSocialSurveyandGallupquestions)andfail todelineateintheirwordingeithertypesofcrime(e.g.,homicide,assault, burglary)orspecificsourcesofcrime(e.g.,“random”assaultsbygangmembersorotherstrangersversus“nonrandom”assaultsbyintimates).Infact, neitherofthetwomostwidelyusedquestionsinsurveysevenmentionsthe word crime ,makingitdifficulttounderstandrespondents’answers(Ferraro, 1995; LaGrange & Ferraro, 1987, 1989; Warr, 1994).2Thisstudyattemptstoaddresstheseconcernsbycomparingthegeneral fearofcrimetothespecificfearofneighborhoodgangs,groupsthathave beentargetedbypoliticiansandthemediaascommittingrandomviolence. Randomviolenceassociatedwithgangsseemsespeciallylikelytoevokedifferentlevelsoffearthanothertypesofcrime.Inherentinthedefinitionof random isthepossibilitythatitcanaffectanyone,includingthosewhodonot frequenttraditionallyhigh-crimeareasandwhomayeventakespecificpre cautionstoavoidvictimization.Themediaoftenportraygangviolencewith theimageofaninnocentbystandercaughtinadrive-byshootingorinthe crossfireofgangwarfare.Thekillingof“honorstudent”CorieWilliamsby gangmembersonabusinLosAngelesillustratesthispoint.Coriewasdis cussedatlengthinthenationalmediaandbythepublicnotonlybecauseshe diedonthesamedayasEnnisCosbybutalsobecauseshesymbolizesthe capriciousnatureofgangviolence.3Ifanhonorstudentcanbekilled,anyone can,thusreinforcingtherandomnessofcrimeinpeople’sminds.Gangsmay alsobemorelikelytoinvokefearinresidentsbecausegangsareoftenvisible, hangingoutonstreetcornersingroups,wearingdistinctivedressandhair styles,leavingidentifyinggraffitionwallsandbuildings,andmakingan efforttointimidateotherswithinandoutsidetheirneighborhoods(Decker& VanWinkle,1996).AsFerraro(1995,p.115)noted,“GangactivityandtheLane, Meeker / SUBCULTURAL DIVERSITY501

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threatofrobbery,car-jackingorassaul t... enterthemindsofurbandwellers during the course of routine daily living.” FACTORS CONTRIBUTING TO FEAR OF CRIME AND FEAR OF GANGS DIFFER Priorresearchhasillustratedsomerelativelyconsistentyetparadoxical findingsregardingtheassociationbetweenindividualdemographicfactors andfearofcrime.Studieshaveshownwomenandolderindividualsaremore afraidofcrimethanmalesandyoungerpeople,althoughwomenandolder peoplefacethelowestobjectiveriskofcriminalvictimization(Ferraro, 1995;LaGrange&Ferraro,1989;Miethe,1995).Thisconsistentfindingis calledthe paradoxoffear (Warr,1994,p.12;seealsoSkogan&Maxfield, 1981;Stafford&Galle,1984).Thefindingregardingwomen’sfearisconsis tentovertime,andresearchersgenerallyassumeitreflectswomen’sconcernsaboutsexualassault(Ferraro,1995;Madriz,1997;Rountree,1998; Stanko,1995;Warr,1985).Thisassumptionissupportedbyfindingsoflack ofgenderdifferenceswhenspecificcrimes,excludingsexualassault,are studied.Inrecentresearch,forexample,HaghighiandSorensen(1996), RountreeandLand(1996),andRountree(1998)foundgendertobe nonsignificant in predicting burglary-specific fear. Thedataregardingolderpeoplearemoreequivocal.Yin(1985)and LaGrangeandFerraro(1987,1989)havearguedthattheolderpeople’sfear ofcrimeisoverstated,andFerraro(1995),Haghighi,andSorensen(1996); RountreeandLand(1996);andRountree(1998)foundyoungerpeopletobe morefearful.Chiricosetal.(1997)foundthatfearwassignificantlylowerfor olderWhiteswithhigherincomes,andMcCoy,Wooldredge,Cullen, Dubeck,andBrowning(1996)foundthatolderpeoplearenotasfearfulas somehavediscovered.Yet,othershavearguedthatolderpeople’sfearlevels donotmatchtheirvictimizationlevelsbecauseolderpeopleoftenhavetaken steps to protect themselves (Skogan, 1990; Wilson & Kelling, 1982). Withregardtorace,minorities(especiallyAfricanAmericans)aretypi callymorefearfulthanWhites(Haghighi&Sorensen,1996;Skogan,1995; Warr,1994),althoughRountreeandLand(1996)foundnon-Whiteswere lessfearfulofburglarythanWhites.Peoplewholiveinlow-incomeareasare generallythoughttobemorefearfulbecausetheyfacemoreproblematic communitydynamics,suchassocialdisorganization(Taylor&Covington, 1993;Warr,1994;Will&McGrath,1995).Asnotedearlier,therelationship betweenpriorvictimizationandfearisproblematicbecausethosemostvic timized(e.g.,youngmales)arenotnecessarilythemostfearful(Taylor&502CRIME & DELINQUENCY / OCTOBER 2000

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Hale,1986;Warr,1994).Giventhesemixedfindingsontheimportanceof demographics,itislikelythatthesevariableswilldifferentiallypredictthe general fear of crime and the specific fear of gangs. IMPORTANCE OF SUBCULTURAL DIVERSITY Oneapproachtoexaminingthevictimization-fearparadoxhasbeento analyzecommunityfactorsthoughttobeassociatedwithfear.Mostofthe theoriespointingtotheimportanceofcommunityfactorsforexplainingfear ofcrimearesituatedwithinthesocialdisorganizationtradition.Thisperspec tivefocusesonneighborhoodfactorssuchaslowsocioeconomicstatus,resi dentialmobility,andracialheterogeneityaskeyinpredictingcrimeandfear ofcrime(Bursik&Grasmick,1993;Sampson&Groves,1989;Shaw& McKay,1942).Thesubculturaldiversitytheorytestedhereissituatedinthe socialdisorganizationtraditionandpositsthatfearofcrimeprimarilyresults fromindividuals’worriesaboutlivingnearpeoplefromdifferentcultural(or racial)backgrounds(Merry,1981;seealsoBursik&Grasmick,1993; Skogan,1995).Accordingtothisview,themannersandbehaviorsofthese “others”aredifficulttointerpret,whichleadstouncertaintyintheenvironmentandthereforefear.Merry(1981,p.149)arguedthatracialandethnic differencesareaproblembecauseresidentsinterprettheirneighbors’behavior“throughthelensoftheirownculture.”Forexample,shefoundthatChineseresidentswhoweretypicallyquietandreserveddidnotunderstandthe loud,boisterousbehavioroftheBlacksintheirhousingcomplexandthereforefoundthemdangerous.Whenpeoplefearothers,theyarelesslikelyto feeltheyhavetheindividualandcollectiveefficacyintheirneighborhoodsto maintainsocialcontrolandcombatproblems,suchasgroupsofteenagers, gangs, and crime (see Sampson, Raudenbush, & Earls, 1997). Giventherecentoriginofthesubculturaldiversitymodeltoexplainfear ofcrime,therearefewstudiesspecificallytestingthistheory.However,there arefindingsintheliteraturethatsupportthismodel.Liska,Lawrence,and Sanchirico(1982,p.767)foundthat“theracialcompositionofcitiesinflu encesfearofbothWhitesandnonWhites.”Intheirstudy,theproportionof interracial,WhitevictimizationsandthecrimeratedirectlyaffectedWhites’ fear.Alternatively,segregationandpercentagenon-Whitedirectlyaffected non-Whites’fear.Althoughtheydidnotdirectlymeasurefearintheirstudy ofattachmenttoplace,Taylor,Gottfredson,andBrower(1985,pp.539-540) found“thatracialdiversityattheblocklevelwasassociatedwithlowerlevels ofattachment”totheresidentialenvironmentandsuggestedthatthismaybe dueto“confusionabouttheappropriatenormstofollow,”whichdirectlysup ports the subcultural diversity argument.Lane, Meeker / SUBCULTURAL DIVERSITY503

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CovingtonandTaylor(1991)specificallytestedthesubculturaldiversity thesis,alongwiththeotherthreedominanttheoreticalmodelsthatpositcom munityfactorsastheprimarycausesoffear,4andfoundsomesupportforall fourmodels.Theyconcludedthatsubculturaldifferencesamongpeopleliv inginthesameneighborhoodincreasefearandarguedthatfearwasgreaterin areaswheretheracialmixwaschangingratherthanstable.Taylorand Covington(1993)subsequentlyfoundthatneighborhoodsexperiencing unexpectedincreasesinminorityandyouthpopulationshadhigherfearlev els,supportingthesubculturaldiversitytheoryandconfirmingtheirearlier arguments. Inamorerecentstudy,St.JohnandHeald-Moore(1996)foundthatpreju dicedWhitesweremorelikelytobefearfulwhentheyencounteredaBlack strangerthanwerenonprejudicedWhites,althoughbothweremorefearful whentheycameuponaBlackversusaWhitestranger.Moreover,intheir recentexaminationofneighborhoodracialcompositionandfearofcrime, Chiricosetal.(1997)foundthatwhentheycontrolledfordemographicsand perceptionsofcrimeintheneighborhood,perceivedracialcompositionwas significantlyrelatedtofearforWhites—especiallythosewhofelttheywere intheminority—butnotBlacks.Thisstudybuildsonthisrecentliterature regardingtheimportanceofsubculturaldiversitytofearofcrimebyexaminingitseffectsonthegeneralfearofcrimeandthespecificfearofneighborhood gangs in Orange County, California. METHOD The Research Setting OrangeCounty,California,isanidealsettingforthestudyofsubcultural diversityandgang-relatedfearofcrimebecauseofitsincreasingracialand ethnicheterogeneity5andthefactthatmostgangsinSouthernCalifornia havearisenwithintheHispanicculture(Jankowski,1991;Klein,1995; Moore,1978;Moore,Vigil,&Garcia,1983;Spergel,1995).Withthe1994 passageofProposition187inCaliforniarestrictingcivilrightsandsocialser vicesforallundocumented(oftenLatino)immigrants,thereisstrongevi denceofracialandethnicconcernsacrossthestate.Asonelegalimmigrant toldanewspaperreporteruponthepassageofthislaw,“TheMexicansdon’t understandtheAmericans,andtheAmericansdon’tunderstandtheMexi cans”(asquotedinFerrell&Lopez,1994,p.A21).Withtheseracialandeth nicconcernsandtheearliermentionedlawenforcementfocusongangs,the subculturaldiversityperspectiveiswellsuitedtothestudyoffearofcrime and gangs in this area.504CRIME & DELINQUENCY / OCTOBER 2000

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Pollsconductedbeforethecurrentdatawerecollectedin1995indicate thatresidentsofOrangeCountywereconcernedaboutcrimeduringtheearly tomid-1990s.In1993,1994,and1996,residentsrankedcrimeasthemost seriousproblemfacingthecounty,andin1995,crimewassecondonlytothe OrangeCountybankruptcycrisis(Baldassare&Katz,1993,1994,1995b, 1996).Otherthansurveydatacollectedby TheOrangeCountyRegister ,there hasbeenonlyonesurveyaskingresidentsspecificallyaboutgang-related concerns(in1994),sothereisnostrongbaselinewithwhichtocomparecur rentconcernsaboutgangs.However,the1994surveyindicatedthat75%of respondentshadheardofgangsorgang-relatedproblemsintheircommuni ties,and46%believedthatyouthviolencehadincreasedinthepastfew years.Abouthalfoftheparentsinthesurveyworried“verymuch”thattheir childrencouldbeinphysicaldangerbecauseofgangsandyouthviolence (Baldassare&Associates,1994).Theseearlierpolls,coupledwiththecrimi naljusticesystem’spublicizingtheincreasedproblemofgangcrime,clearly sets the stage for increasing public awareness of these issues. Sampling and Data Collection Procedures Thedatausedherewereoriginallycollectedbyamarketingresearchfirm for TheOrangeCountyRegister ,thecounty’slocalnewspaper.Theinstrumentwasdesignedasamarketsurveyandwasconductedintwophasesfrom September19toDecember11,1995.Thefirstphaseconsistedofa24-minute telephonesurveyof1,223randomlyselectedadultsfromOrangeCounty, whichprimarilyaskeddemographicquestions.Adultrespondentswithin eachhouseholdwereselectedbythe“mostrecent”birthdaymethod(see Table1forsamplecharacteristics).6Inthesecondphase,allrespondentswere maileda16-pageself-administeredquestionnaireandthenrecontactedvia telephonetoobtaintheirresponsestothesemorein-depthattitudinalques tions.Thefirmchosethistwo-phaseapproachprimarilybecausethey expectedtogetabetterresponserate.AccordingtoFrey(1989,p.240)a “majortrend”insurveyresearchistheuseofthis“mixed-mode”or“dual frame” approach.Theuseofmorethanonetechniqueallowssurveyresearchersto overcomethedisadvantagesofanyonetechniqueandincreasestheprobabil ity of getting responses from the original sample (Frey, 1989). Dependent Variables Therearetwodependentvariablesinthisstudy,onemeasuringfearofcrime andonemeasuringfearofgangs.Thesurveyquestionaskedthefollowing:Lane, Meeker / SUBCULTURAL DIVERSITY505

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506CRIME & DELINQUENCY / OCTOBER 2000 TABLE 1: Sample Characteristics CharacteristicCodeNPercentageAge 18-24117214.1 25-29215412.6 30-34318214.9 35-39415612.8 40-44513911.4 45-4961169.5 50-547816.6 55-598766.2 60-649393.2 65-6910504.1 70 or older11584.7 Gender Male056045.8 Female166354.2 Race and/or ethnicityaNon-White028823.5 White193576.5 Education Not a high school graduate1514.2 High school graduate226521.7 Vocational and/or technical3252.0 Some college437630.7 College graduate537430.6 Postgraduate613210.8 Income ($) Under 10,0001494.0 10,000-19,9992746.1 20,000-24,9993816.6 25,000-34,999413110.7 35,000-49,999530925.3 50,000-74,999628123.0 75,000-99,999716813.7 100,000 or more813010.6 Home ownership Own163151.6 Rent or other059248.4 Geographical region Inland central133127.1 Other geographical region089272.9 a.OursamplewasprimarilyWhite(76%),whichrepresentstheirproportioninthepopu lation(U.S.BureauoftheCensus,1994).However,thenon-Whiteportionofthesample underrepresentsLatinos,whorepresentthelargestminoritypopulationinOrange County.AccordingtostaffatTheOrangeCountyRegister,Latinoshaveadifferential participationrateinsurveysbecausetheyaredifficulttoreach.Thislowparticipation ratemaybedueinparttothefactthattheyareeithertoopoortoownphonesorunwilling toanswerpersonalquestionsduetoculturalrestraints.Inaddition,thestaffspeculate thatthesizeableundocumentedimmigrantpopulationislesslikelytoanswerquestions due to fear of deportation.

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Belowisalistofday-to-dayproblemsthatmayormaynotparticularlyconcern you.Pleasechecktheboxthatindicateshowmuchyou,yourself,haveactually worried about each problem in the past year or so.Foreachday-to-dayproblemlisted,respondentswereaskedtomarkwhether theyworried frequently occasionally hardlyever ,or never (a4-pointscale). Twooftheday-to-dayproblemslistedwere“crime”and“neighborhood gangs.”Theanswersregardingthesetwoproblemswerereversecoded(1= never ,4= frequently )andconstitutethedependentvariablesforthisstudy.7Independent Variables Theindependentvariablesconsistofdemographiccharacteristicsanda compositevariablemeasuringconcernaboutsubculturaldiversity.Demo graphiccharacteristicswereincludedbecausepriorresearchhasnotedthe importanceofexaminingthecontributionoftheseindividualfactorsto explainingfearofcrime.Thedemographiccharacteristicsenteredintoequationsincludeage,education,gender,income,raceand/orethnicity,home ownership,andcountyregionofresidence(seeTable1).8Countyregionof residencewasincludedasameasureofthecommunitydynamicspeopleface inOrangeCounty—thoselivingintheinlandcentralregionaremorelikelyto experience social disorganization and gangs. Threeoftheday-to-dayproblemquestionsconstitutethevariablemeasuringconcernaboutsubculturaldiversity.Thesurveyaskedrespondentshow muchtheyworriedabout“problemsinracialandethnicrelations,”“foreign immigrantsinOrangeCounty,”and“changingmoralstandards.”Tocreatea compositevariablerepresentingtheconstructofsubculturaldiversity,we againreversecodedtheanswersthensummedthethreescorestogetherand dividedbythree,creatingameanscoreforeachrespondent.9Wechosethese variablesasindicatorsofsubculturaldiversitybasedonthequalitativework ofMerry(1981).Shearguedthatracial,ethnic,andculturaldifferencesb etween communityresidentsoftencausepeopletobelievetheyareindangerofbeing victimizedbycrimeandhurtbyotherrelatedproblems,suchasinsultsand intrusionsontheirownwaysoflife(seeMerry,1981,pp.143-150).Accord ingtoMerry,thissenseofdangerisinpartaresultofculturaldifferencesin moralstandards,suchasnormsabouthowtoact,whattowear,andhowto achievesuccess.InOrangeCounty,previousresearchhasindicatedthat muchofconcernaboutsubculturaldiversityisrelatedtoundocumented Latinoimmigrants,whoresidentsbelievearemorelikelytoparticipatein localgangsandtobringdisorderanddifferentmoralandbehavioralstan dards with them, thereby causing neighborhoods to decline (Lane, 1998).Lane, Meeker / SUBCULTURAL DIVERSITY507

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ANALYSIS Weconductedthreetypesofanalysistodeterminetheeffectsofdemo graphicvariablesandconcernaboutsubculturaldiversityonthefearofcrime andgangs.First,weranbivariatecorrelationsandone-wayANOVAswith crimeworryandgangworrytodeterminethebivariaterelationshipsbetween theindependentvariablesandfearofcrimeandgangs(seeTables2&3). Second,weranstepwiseordinaryleastsquaresregressionequationsforeach508CRIME & DELINQUENCY / OCTOBER 2000 TABLE 2: One-Way ANOVA for Dichotomous Regression Variables 95% Confidence VariableSampleIntervalMeanFValueProbabilityFear of crime GenderFemales3.382 to 3.4923.4410.5069.0012 Males3.240 to 3.3623.30 RaceWhite3.329 to 3.4223.38.0066 .nsNon-White3.284 to 3.4593.37 Home ownershipOwner3.336 to 3.4473.39.6961 .nsOther3.296 to 3.4173.36 Geographical regionInland central3.311 to 3.4633.39.1250 .nsOther3.321 to 3.4193.37 Fear of gangs GenderFemales3.052 to 3.1833.125.9846.0146 Males2.925 to 3.0683.00 RaceWhite3.004 to 3.1143.06.0613 .nsNon-White2.970 to 3.1773.07 Home ownershipOwner2.936 to 3.0743.005.8016.0162 Other3.056 to 3.1923.12 GeographicalInland3.131 to 3.3013.2214.3394.0002 regioncentral Other2.947 to 3.0643.01 TABLE 3: Zero-Order Correlations of Continuous Regression VariablesFear of CrimeFear of Gangs rSignificancerSignificanceAge.14.000.06.027 Education–.05 .ns–.12.000 Income–.06.026–.08.007 Diversity.46.000.47.000

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dependentvariabletodeterminetherelativecontributionofeachpredictorto eachtypeoffearandtoexaminethedifferenceinthepredictivevalueofthese independentvariablesforthetwotypesoffear(seeTables4&5).Finally,we conductedpathanalysestotestthesubculturaldiversitytheoreticalmodel,Lane, Meeker / SUBCULTURAL DIVERSITY509 TABLE 5: Results of Stepwise Linear Regression Analysis for Fear of Gangs VariableR2ChangebaataStep 1.03*** Age.007.024.80 Gender.062.0361.40 Race–.026–.013–.49 Education–.029–.047–1.78 Income–.016–.033–1.17 Home ownership–.179–.103–3.46*** Step 2.01*** Geographical region.151.0773.03** Step 3.21*** Concern about diversity.621.46918.29*** Constant = 1.540F= 49.73*** ModelR2= .247 Model adjustedR2= .242 N= 1,223. a.Coefficients from final model (b, ,t). **p< .01.***p< .001. TABLE 4: Results of Stepwise Linear Regression Analysis for Fear of Crime VariableR2ChangebaataStep 1.03*** Age.018.0722.42* Gender.068.0471.79 Race–.080–.467–1.75 Education.002.004.14 Income–.028–.070–2.41* Home ownership–.038–.026–.87 Step 2.00 Geographical region–.025–.015–.59 Step 3.19*** Concern about diversity.502.45117.32*** Constant = 2.089 F= 43.75***ModelR2= .225 Model adjustedR2= .219 NOTE:N= 1,223. a.Coefficients from final model. *p< .05.***p< .001.

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whichsuggeststhatdemographicvariablesinfluenceconcernaboutsubcul tural diversity, which in turn influences fear (see Figure 1). RESULTS Weexaminedtworesearchquestions.First,aregeneralfearofcrimeand thespecificfearofgangsdifferent?Second,howdoesconcernabout subculturaldiversityorracialheterogeneityaffectthesetypesoffear?Fearof crimeandfearofgangs,althoughsignificantlyrelated,arenothighlycorre latedforthissample( r =.40).Thezero-ordercorrelationsforcontinuous regressionvariablesandaseriesofone-wayANOVAtestsfordichotomous regressionvariablesindicatethatatthebivariatelevel,females,olderindivid -510CRIME & DELINQUENCY / OCTOBER 2000 Figure 1:Path Analyses Predicting Fear of Crime and Fear of Gangs

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uals,peoplewithlowerincomelevels,andpeoplewhowereconcernedabout subculturaldiversityweresignificantlymorefearfulofcrimeandgangs. However,beingfemaleandbeingolderweremoreimportantforfearofcrime thanfearofgangs.Forfearofgangsbutnotfearofcrime,thosewithlower educationlevels,thosewhodidnotownhomes,andthosewholivedinthe inlandcentralregionofthecounty,wheremoresocialdisorganizationand gangactivityoccurs,alsoweremoreconcerned.Itisinterestingthatrace (ethnicity)isnotsignificantlyrelatedtofearofcrimeorfearofgangs,evenat thebivariatelevel(seeTables2&3).Bivariateresultswouldleadusto believe,aspriorresearchhasshown,thatbeingfemaleandbeingolderare importantvariablespredictingfearandthatbeinginmoreunstableenviron ments(e.g.,rentingahome,livinginamorediverseandcrime-riddenarea)is more important to gang-related fear than broader crime-related fear. Stepwise Regressions Predicting Fear of Crime and Fear of Gangs Thenextstepistopredictfearofcrimeandfearofgangsbasedonthe demographicvariablesalreadystatedandsubculturaldiversityvariable whilecontrollingforotherfactors.Tables4and5reporttheresultsofthe stepwiselinearregressionanalysespredictingfearofcrimeandfearofgangs. Duetotheimportanceofage,gender,race,education,income,andhome ownershiponfearofcrime(seeWarr,1994),weenteredthesevariableson thefirststep.Forfearofcrime,thesevariablestogetherexplainonly3%of thevariancebutaresignificant( R2=.03, p <.001).Forfearofgangs,these variables also predict only 3% the variance ( R2= .03, p < .001). Becauseofthestrongregionaldifferencesincrime,andgangcrimeespe cially,weenteredtherespondents’countyregionofresidencenext.Forfear ofcrime,thecountyregionofresidencedoesnotexplainanyadditionalvari anceandisnotsignificant.Butforfearofgangs,countyregionofresidence significantly increases the R2by 1% ( R2change = .01, p < .001). Weenteredsubculturaldiversitylastbecausewewantedtodetermineif thisfactorwasasignificantpredictoroffearofcrimeandgangsaftercontrol lingfortheothervariables.Forfearofcrime,thisvariablecausedasignifi cantchangeinthe R2( R2change=.19, p <.001),increasingtheexplained varianceinfearby19%,leadingtoatotaladjusted R2of.219forthefinal model.Forfearofgangs,subculturaldiversityexplainsanevenlarger,signif icantincreaseinthe R2thanitdoesforfearofcrime( R2change=.21, p < .001), leading to a final adjusted R2of .242 for the model. Tables4and5alsoreporttheregressioncoefficientsforthefinalfearof crimeandfearofgangsregressionmodels,withdemographics,regionofres idence,andconcernaboutdiversityincludedaspredictors.Althoughage( t =Lane, Meeker / SUBCULTURAL DIVERSITY511

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2.42, p <.05)andincome( t =–2.41, p <.05)arestillsignificantlyrelatedto crime-relatedfear,theyarenolongerimportanttogang-relatedfear.So,the olderonewasandthelowerhisorherincome,themorefearfulthatperson waslikelytobeofcrimeingeneralbutnotgangsinparticular.Althoughgen derwasimportanttobothfearofcrimeandgangsinthebivariateanalysis, genderisnolongersignificantinthefinalregressionmodels.Beingfemaleis notapredictorofeitherkindoffearoncewecontrolforotherfactors.As expected,basedonthebivariateanalyses,raceisnotimportanttoeithertype offear.Wefoundthateducationandhomeownershipweresignificantlyand negativelyrelatedtoonlygang-relatedfearatthebivariatelevel.Inthe regressionequation,onlyhomeownershipremainssignificant( t =–3.46, p < .001),sothosewhodonotownhomesarestillmorefearfulofgangsafter controlling for other factors. Asinthebivariateanalyses,regionofresidenceisnotasignificantpredic toroffearofcrimebutisasignificantpredictoroffearofgangs( t =3.03, p < .01).Thosewholivedintheinlandcentralregion,whichisgenerallyassociatedwithmoresocialdisorganizationandgangproblems,weremoreconcernedthanthosewhodidnotliveinthisareaaboutgangsbutnotaboutcrime ingeneral.Theconcernaboutdiversityvariableissignificantlyandpositivelyrelatedtofearofcrime( t =17.32, p <.001)andfearofgangs( t =18.29, p <.001).Thoseindividualswhoweremoreconcernedaboutraceandethnic relations,immigrants,andchangingmoralstandardsweremuchmorelikely toworryaboutcrimeandgangs.Insum,thestepwiselinearregressionequationsindicatethatdemographicfactorsdifferentiallypredictfearofcrime andfearofgangs.And,thesemodelsshowthatconcernaboutdiversity explainsalotofvarianceinbothequations—moreinthefearofgangsmodel (21%) than in the fear of crime model (19%). Path Analyses Predicting Fear of Crime and Fear of Gangs Thestepwiseregressionanalysesconfirmthatbothresidentiallocation andconcernsaboutsubculturaldiversityareimportantpredictorsoffearof gangs,whereasonlythelatterisimportanttofearofcrime.Thefinalstep employspathanalysistodeterminetheroleofthesevariablesasintervening causaleffectsbetweendemographicsandfearofcrimeandgangs.Asnoted earlier,thehypothesisthatguidedthedevelopmentofthepathmodelwasthat demographicfactorswouldpredictthegeographicalregionofresidence (whichtheoreticallyvariesinracialheterogeneityandcrime),whichinturn wouldpredictconcernaboutsubculturaldiversity,whichwouldpredictfear. Again,theresultsoftheanalysesaredifferentdependingonwhetherwe examine fear of crime or fear of gangs.512CRIME & DELINQUENCY / OCTOBER 2000

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Forsimplicity,Figure1reportsthestandardizedcoefficientsforthepaths withsignificant t -valuesineachpathmodelorthosevariablesthathavesig nificantdirectorindirectrelationshipswiththedependentvariables—fearof crimeandfearofgangs.Consistentwiththestepwiseregressionfindings, gender(beingfemale)isnotimportanttoeithermodel.Eachpathmodelpro videsagoodfit.Forfearofcrime,theadjustedgoodness-of-fitindex(AGFI) is.99,thegoodness-of-fitindex(GFI)statisticis1.00,andthechi-square goodness-of-fitstatisticis6.33(6 df p =.39).10Forfearofgangs,theAGFIis .99, the GFI is 1.00, and the chi-square is 8.94 (8 df p = .35). Aswouldbeexpected,theindirectpathstofearofcrimeandfearofgangs fromtheexogenousdemographicvariablesofage,education,andincometo theendogenousvariableofconcernaboutdiversityaresignificantandofthe samemagnitudeforbothmodels.Ageandincomearepositivelyrelatedto concernaboutdiversity,whereaseducationisnegativelyrelatedtothese diversityconcerns.Thepathsfromtheexogenousdemographicvariablesof education,income,andracetotheendogenousvariablegeographicalregion aresignificantandnegativeforbothmodels.Asweexpected,peoplewith lowereducationallevels,lowerincomes,andnon-Whitesweremorelikelyto liveintheinlandcentralregion.Forbothmodels,concernaboutdiversityhas a significant direct positive effect on fear. Asinthestepwiseregressionmodels,peoplewhoweremoreconcerned aboutdiversityweremoreconcernedaboutgangsthancrimeingeneral. However,thepathanalysesshowdifferencesinrelationshipsamongfear, subculturaldiversity,andothervariables.Forfearofcrimebutnotfearof gangs,agehasadirectpositiveeffectandincomehasadirectnegativeeffect onfear.Consistentwiththeliterature,olderpeopleandindividualswith lowerincomesweremorelikelytofearcrimeingeneral.Forfearofgangsbut notfearofcrime,educationandhomeownershiphavedirectnegativeeffects. Peoplewithlowereducationlevelsandrentersweremorelikelytoworry aboutgangs.Geographicalregionofresidenceorlivingintheinlandcentral regionhasadirectpositiveeffectonfearofgangs,andeducation,income, andracehavenegativeindirecteffectsonfearofgangsthroughgeographical region.Findingsforbothmodelsareconsistentwithpriorresearchinthatthe R2sweremodest—.22forfearofcrimeand.24forfearofgangs(seeChiricos etal.,1997).Insum,thepathmodelsshowrelationshipsbetweendemo graphicvariablesandfearthatwerenonsignificantintheregressionmodels andfear.Forfearofcrime,educationnowhasanindirectnegativeeffect throughconcernaboutdiversity.Forfearofgangs,ageandincomehavea positiveindirecteffectandeducationhasanegativeindirecteffectthrough concernaboutdiversity.Inaddition,education,income,andracehavenega tive indirect effects through geographic region.Lane, Meeker / SUBCULTURAL DIVERSITY513

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DISCUSSION AND CONCLUSION Inallthreetypesofanalysesconducted,theresultsweredifferentdepend ingonthedependentvariable—fearofcrimeorfearofgangs.Although muchofthepreviousresearchhasbeenproblematicinitsmeasurementof fearofcrime,ithasshownrelativelyconsistentfindingswithregardtodemo graphics.Ingeneral,womenandolderpeoplehavebeenmostfearful,although theyfacethelowestobjectiveriskofvictimizationbystreetcrime.Itisinter estingthatthe t -valuesinthefirstandsecondstepsoftheregressionsindicate thatwhendiversityisnotinthemodel,genderisasignificantpredictorof bothfearofcrimeandfearofgangs.But,thecurrentresultsarenoteworthyin thattheydonotshowagendereffectoneitherfearofcrimeorfearofgangs whenwecontrolforconcernaboutdiversity.Otherrecentstudieshavealso foundthatgenderisnotsignificantlyrelatedtofear(e.g.,Rountree&Land, 1996).Wesuspectthatthepoliticalwaroncrimeandgangsandthemedia’s attentiontotheseissues,andespeciallytheattentionto“random”violent crimesandimmigration“problems,”havemadeconcernaboutgangsmore universalamongmenandwomeninOrangeCounty.AsMadriz(1997) noted,crime(andinthiscasegangcrime)mayhavebecome“codelanguage” forbothraceandclass(here,poorLatinoimmigrants)(seealsoBaer& Chambliss,1997).Ontheotherhand,itmaybe,asRountreeandLand(1996) argue,thatgenderisdifferentiallypredictiveoffeardependingonhowitis measured.Here,fearismeasuredas“worry.”Itispossiblethatthemeninthis studyfeltlessthreatenedbythequestionwording—feelingmorecomfortabletoadmit“worry”thanfear—andweremorehonestabouttheirconcerns. Itisalsopossiblethatforsomepeople,however,thisquestionmeasured altruisticfear,andpeoplewere“worrying”abouttheirchildrenorspouses (see Ferraro, 1995). Althoughthetypicalfindingthatwomenaremoreafraidthanmenrarely wasquestioneduntilrecentstudiesexaminingspecificcrimetypesfound differentresults(e.g.,Rountree,1998;Rountree&Land,1996),some expertshavecontinuedtoarguethatolderpeoplearenotasfearfulassome researchersassume(LaGrange&Ferraro,1987,1989;McCoyetal.,1996; Rountree&Land,1996;Yin,1985).Thecurrentanalysisindicatesthatage doeshaveasmall,directsignificanteffectonfearofcrimebutnotonfearof gangs.However,ageislinkedtoconcernaboutdiversityandthereforeaffects bothfearofcrimeandfearofgangsindirectly.Consequently,studiesthatdo notallowforindirectrelationshipstoemergeintheanalysisdesignbutfind thatolderpeoplearenotsofearfulmaymisssomeimportantintricaciesthat better gauge this complex issue.514CRIME & DELINQUENCY / OCTOBER 2000

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Asinpreviousstudies,theeffectsofincome,education,andraceare mixed.Aninterestingfindingwithregardtoincomeisthatitissignificantly andnegativelyrelatedtofearofcrimebutnottofearofgangs.Theeffectsof incomeonfearofgangsarepositiveandindirectthroughconcernabout diversity.Thisrelationshipalsoholdsforfearofcrime.So,peoplewhohave moreincomearemorelikelytoworryaboutdiversityissues,whichleads themtoworryaboutcrimeandgangs.Peoplewithlowerincomesaremore likelytoliveinthelowerincomeareas,whicharemorelikelytohavemajor “problems”withgangcrime.Lowerincomeindividualsarealsomorelikely tobeminoritiesinOrangeCounty.And,forfearofgangs,incomeandracedo haveindirectnegativeeffectsonfearthroughgeographicalregionofresi dence.Inotherwords,minoritiesandlowerincomeindividualsaremore likelytoliveintheinlandcentralregion,andthosewhodoaremorelikelyto beafraidofgangs.Mostofthepreviousresearchfocusingonraceeffectshas examinedthedifferencebetweenWhitesandprimarilyAfricanAmericans, evenwhentheanalysisdistinguishesbetweenWhitesandnon-Whites(e.g., Liskaetal.,1982,Rountree,1998).ThisanalysislooksatWhitesand(primarily)Latinos,andourresultsmayindicatethatraceeffectsareafunction oftheminoritygroupstudied.Futureresearchprojectsmightcloselyexaminedifferencesamongmanyracialandethnicgroupstoseehowthesegroups differ. Thenegativerelationshipbetweenhomeownershipandfearofgangsis interesting,too.Becauseoffinancialandnuisanceproblemswithgraffiti, onemightexpecthomeownerstobemoreworriedaboutneighborhood gangs.Yetinthisanalysis,rentersaremorelikelytoworryaboutgangs.This findingisindependentofincomeandthegeographicallocationofrenters.It suggeststhatrentingmaybeasurrogateindicatorforothersocialdisorgani zationvariables,suchasincreasedmobility,single-parenthouseholds, greaterdensity,andlargernumbersofchildren,whichmaybemoreassoci ated with fear of gang crime. Therelationshipbetweenconcernaboutdiversityandbothfearofcrime andfearofgangssupportsthosewhoarguethatracialandculturalmisunder standingsarethekeyfactorsinpredictingfearofcrime.Merry(1981)argued thatpeople’ssenseofdangerisrelatedtotheirfearsofstrangersandthat racialandethnicdifferencesaccentuatethesefearsduetopeople’sinability tounderstandthebehaviorsofindividualswhobelongtodifferentcultural groups. These data support her theory. Theeffectofconcernaboutdiversityonfearofgangs,inparticular,is likelybecausethemajorityofgangsinthelocalareaareLatinobarriogangs andbecausethemajorityofthissampleisWhite(Capizzi,1996;seealso Vigil,1988).ItispossiblethatthisfindingisduetoanassociationintheLane, Meeker / SUBCULTURAL DIVERSITY515

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(White)public’smindbetweengangsandHispanics.Everydayconversa tionswithWhitesindicatethatmanypeopleintheareaavoidthoseareasthat areprimarilyLatinobecausetheyareafraidofcrimeandgangs.Forexample, onewomanindicatedtooneoftheauthorsthatshewouldonlygotoacityin theinlandcentralregionofthecounty,wheremanygangsclaimterritory, duringthedayandeventhenwouldtakeoffallherjewelryanddressinold clothestoavoidvictimization.Stillotherstalkaboutavoidingcertainstreets andtakingthelongwaytotheshoppingareasatnighttoavoidgangswho resideinthebarrios(Lane,1998).Basedonthesesurveydata,inOrange County,thereisadirect,independent,andpositiveconnectioninthepublic’s mindbetweenconcernsaboutdiversity(e.g.,Latinoimmigration)andwor riesaboutcrimeandgangs.Thislinkisindependentofothertheoretically importantdemographicvariables(e.g.,age,gender,education)foundinpre viousliterature(seeWarr,1994).Ourfindingsshowthattherelationship betweenraceandfeariscomplex.Forexample,fearofotherraces(orethnici ties)iskeytoourmodels,butdifferencesbetweenWhitesandminoritiesare not significant. Thesupportforthesubculturaldiversitymodelinexplainingfearofcrime and,moreimportant,fearofgangshasimportantimplicationsforpolicy makers.Indeed,ascrimehasdecreasedinrecentyearsthroughoutthecountryandinOrangeCounty(Boucher,1998),fearofcrimehasremainedhigh (Baldassare&Katz,1993,1994,1995b,1996).Thesefindingssuggestthat policymakersconcernedaboutdecreasingfearofcrimewillhavetodomore than“just”decreasecrime.People’sfeelingsabouttheirneighborsandtheir neighborhoodsarejustasimportantascrimelevelsorevenmoreimportantin contributingtofearofcrime.Withouteffortstoaddressthesefactors,fearis likely to remain high. NOTES1.Thelocalpolicechiefsroutinelymentionthesetwoincidentsaskeyeventstriggering community awareness about gang crime in Orange County (see Lane, 1998). 2.Thetypicalfearofcrimequestionsvaryintheirwordingbutincludeversionsoftwodif ferentquestions.TheNationalCrimeSurveyuses“Howsafedoyoufeelorwouldyoufeelbeing outaloneinyourneighborhoodatnight?”(Ferraro,1995;LaGrange&Ferraro,1989).Although thewordingoftheGeneralSocialSurvey(GSS)questionvaries,itgenerallyreads“Isthereany areaaroundhere—thatis,withinamile—whereyouwouldbeafraidtowalkaloneatnight(or during the day)?” (Ferraro, 1995; Warr, 1994). 3.CorieWilliamswascaughtinthecrossfireofagangretaliationshootingwhileridingona MetropolitanTransportationAuthority(MTA)businLosAngelesonJanuary16,1997,the samedaythatEnnisCosby,thesonofactorBillCosby,wasshotwhilechangingatireonaLos Angelesfreeway(Goldman,1997).Bothincidentsmadethelocalandnationalnewsforweeks as examples of random violence. 516CRIME & DELINQUENCY / OCTOBER 2000

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4.Theotherdominanttheoreticalmodelsare“indirectvictimization”(seeSkogan,1977; Tyler,1980),“incivilities”or“disorder”(seeCovington&Taylor,1991;Lewis&Maxfield, 1980;Skogan,1990),and“communityconcern”(seeConklin,1975;Covington&Taylor,1991; Garofalo & Laub, 1978). 5.From1980to1990,thepercentageofthecountypopulationthatwasHispanic,Asian,or African American increased 14% (Baldassare & Katz, 1995a). 6.Weconductedsecondaryanalysisandhadnocontroloverthesamplingprocedures, whichareasfollows.ForPhase1,theresearchfirmcontacted2,012peoplethrougharan dom-digit-dialprocedureusingacomputer-aidedtelephoneinterviewing(CATI)system.Of these,1,223completedthesurvey,foraresponserateof60.8%.InPhase2,these1,223individu alswererecontactedand69%ofthemcompletedtheremainderofthesurvey.Toensureacom pletesampleforthenewspaper,thefirmmatchedtheremaining31%ofthesample(379respon dents)torespondentswhofinishedthequestionnaireandthemissingattitudinalresponseswere imputedbasedonmatchingdemographiccharacteristics.Thefirmdescribedtheimputingpro cessasfollows.Eachpersonwithmissingdatawasmatchedascloselyaspossibleonalldemo graphicandlocationvariables(morethanareincludedinouranalysis)toanotherrespondent withcompletedata.Thefirmreplacedthemissingdatabysubstitutingthecompletedatafrom thematchedrespondent.Thefirmassertsthatitfollowedstandardsurveymethodologyinusing thismatchingandsubstitutionprocess.Thefinaldatasetof1,223respondentsgiventousdoes notindicatewhichcaseswereassignedresponses.Consequently,wecannotjudgewhetherthere wasdifferentialattritionbetweenthetwophasesofthesurvey.However,thefinaldatasetisrepresentativeoftheOrangeCountypopulationwithregardtoalldemographiccharacteristics reportedinTable1exceptrace.TheWhiteportionofthissampleisequaltotheproportionof Whitesinthepopulation(about76%),butthenon-Whiteportionofthesampleunderrepresents Hispanics,whoareabout23%ofthecountedpopulationbutonly12.5%ofthistotalsample(see U.S. Bureau of the Census, 1994). 7.Theauthorsbelievethat“worry“isveryclosetotheconstructaspeoplemaydefineitfor themselvesandthereforewaslikelyinterpretedtomeanfear.Forexample,laypeopleoftentalk indailyconversationaboutbeing“worried“thattheircarmightbebrokenintooraboutletting theirchildrengooutunsupervisedwheretheymightbevictimized(e.g.,parks;seeLane,1998; Madriz,1997).Itisonthislatterpointthatthecurrentmeasurementmaybeproblematic—itis unclearwhetherpeoplewerethinkingaboutpersonalfearoraltruisticfearwhentheycompleted thesurvey.Butevenwiththisambiguity,webelievethatthesequestionsareatleastasadequate asthetypicalquestionsusedtomeasurefearofcrime(e.g.,GSSandtheNationalCrimeVictim ization Survey). 8. TheOrangeCountyRegister segmentsthecountyintofiveregions.Weseparatedthe respondentsintotwocategories—thosewholivedinthe“inlandcentral”regionandthosewho livedelsewhere.Theinlandcentralregionhasmoreurbandensity,morepoverty,highercrime rates,andthelargestconcentrationsofgangcrime(OrangeCountyChiefs’andSheriff’sAssoci ation, 1998). 9.Weconductedasimplefactoranalysis,andthesethreeitemsloadedonasinglefactor, indicatingtheseitemsrepresentasingleconstruct.Allthecorrelationsbetweenthesethreeitems are significant. 10.WeusedLISREL8toconductthepathanalysis.Basedonpreviousresearch,we designedtheanalysestotestthetheorythatdemographiccharacteristicsaffectregionofresi dence,whichinturnaffectsconcernaboutsubculturaldiversityandfear.Forthisanalysis,we madethenormalassumptions.Theerrorsoftheendogenousvariablesarenotcorrelated,butwe allowtheerrorsoftheexogenoustermstocorrelate.TheGoodness-of-FitIndex(GFI)andthe AdjustedGoodness-of-FitIndex(AGFI)indicatehowwellthemodelfitstheobserveddata.A Lane, Meeker / SUBCULTURAL DIVERSITY517

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GFIandAGFIgreaterthan.90indicatethemodelfitsthedatawell.Likewise,anonsignificant chi-square indicates the model fits well.REFERENCESBaer,J.,&Chambliss,W.J.(1997).Generatingfear:Thepoliticsofcrimereporting. Crime,Law& Social Change 27 87-107. Baldassare,M.,&Associates.(1994). Druguseislifeabusesurvey:Thirdannualstudy,June 1994 Irvine, CA: Author. Baldassare,M.,&Katz,C.(1993). OrangeCountyannualsurvey:1993finalreport .Irvine:Uni versity of California, Irvine. Baldassare,M.,&Katz,C.(1994). OrangeCountyannualsurvey:1994finalreport .Irvine:Uni versity of California, Irvine. Baldassare,M.,&Katz,C.(1995a). Theimpactsofsuburbancontextoncrimeperceptions, mobilityfears,andpolicypreferences .Unpublishedmanuscript,UniversityofCalifornia, Irvine. Baldassare,M.,&Katz,C.(1995b). OrangeCountyannualsurvey:1995finalreport .Irvine: University of California, Irvine. Baldassare,M.,&Katz,C.(1996). OrangeCountyannualsurvey:1996finalreport .Irvine:University of California, Irvine. Best,J.(1999). Randomviolence:Howwetalkaboutnewcrimesandnewvictims .Berkeley: University of California Press. Boucher,G.(1998,January2).Homicideratedownagainfor4thstraightyear. LosAngeles Times, Orange County Edition pp. B1, B3. Bursik,R.J.Jr.,&Grasmick,H.G.(1993). Neighborhoodsandcrime:Thedimensionsofeffective community control Lexington, MA: Lexington Books. CaliforniaCouncilonCriminalJustice.(1995). Reportandrecommendationsofthejuvenilegun violence public hearings Sacramento, CA: Author. CaliforniaStreetTerrorismEnforcementandPreventionAct,CaliforniaPenalCode,Compact Edition § 186.20 (West 1997). Capizzi,M.R.(1996). 1995annualreportgangunit&multiagencyresourcegangenforcement teams Santa Ana, CA: Orange County District Attorney. Chiricos,T.,Hogan,M.,&Gertz,M.(1997).Racialcompositionofneighborhoodandfearof crime. Criminology 35 107-131. Clinton,W.J.(1997,February4). Stateoftheunionaddress [On-line].Availableathttp://www. pub.whitehouse.gov Conklin, J. (1975). The impact of crime New York: Macmillan. Covington,J.,&Taylor,R.B.(1991).Fearofcrimeinurbanresidentialneighborhoods:Implica tionsofbetween-andwithin-neighborhoodsourcesforcurrentmodels. TheSociological Quarterly 32 231-249. Decker,S.H.,&VanWinkle,B.(1996). Lifeinthegang:Family,friends,andviolence .New York: Cambridge University Press. Feinstein,D.(1997,January22). Feinsteinanti-gangbillre-introducedonfirstdayinsenate (AvailablefromDianeFeinsteinofCalifornia,525MarketSt.,Suite3670,SanFrancisco, CA 94105) Ferraro,K.F.(1995). Fearofcrime:Interpretingvictimizationrisk .NewYork:StateUniversity of New York Press. 518CRIME & DELINQUENCY / OCTOBER 2000

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Ferrell,D.,&Lopez,R.J.(1994,November10).StatewaitstoseewhatProp.187willreally mean. Los Angeles Times, Orange County Edition pp. A1, A21. Frey, J. H. (1989). Survey research by telephone (2nd ed.). Newbury Park, CA: Sage. ThegangprobleminAmerica:FormulatinganeffectiveFederalresponse:Hearingbeforethe SubcommitteeonJuvenileJusticeoftheCommitteeontheJudiciary,UnitedStatesSenate 103d Cong., 2d Sess. (1994, February 9) (statement of James C. Frier). Garofalo,J.,&Laub,J.(1978).Thefearofcrime:Broadeningourperspective. Victimology 3 242-253. Goldman,A.(1997,January29).YouthchargedinslayingonL.A.bushastroubledpast. Los Angeles Times, Orange County Edition pp. A3, A16. Haghighi,B.,&Sorensen,J.(1996).America’sfearofcrime.InT.J.Flanagan&D.R. Longmire(Eds.), Americansviewcrimeandjustice:Anationalpublicopinionsurvey (pp. 16-30). Thousand Oaks, CA: Sage. Horton,K.(1991,August7).Slaying:Gangstatuteaddsfelonychargesinrandomkillingcase. The Orange County Register p. B9. How California voted. (1996, March 28). Los Angeles Times, Orange County Edition p. A20. Irwin,J.,Austin,J.,&Baird,C.(1998).Fanningtheflamesoffear. Crime&Delinquency 44 32-48. Jackson,P.,withRudman,C.(1993).MoralpanicsandtheresponsetogangsinCalifornia.In S.Cummings&D.J.Monti(Eds.), Gangs:Theoriginsandimpactofcontemporaryyouth gangs in the United States (pp. 257-275). New York: State University of New York Press. Jankowski,M.S.(1991). Islandsinthestreet:GangsandAmericanurbansociety .Berkeley: University of California Press. Jreskog,K.,&Srbom,D.(1993). Lisrel8:StructuralequationmodelingwiththeSIMPLIS command language Hillsdale, NJ: Lawrence Erlbaum. Juvenilecrime:Breakingthecycleofviolence:HearingbeforetheSubcommitteeonJuvenile JusticeoftheCommitteeontheJudiciary,UnitedStatesSenate ,103dCong.,2dSess.(1994, November 29). Klein,M.W.(1995). TheAmericanstreetgang:Itsnature,prevalence,andcontrol .NewYork: Oxford University Press. LaGrange,R.L.,&Ferraro,K.F.(1987).Theelderly’sfearofcrime:Acriticalexaminationof the research. Research on Aging 9 372-391. LaGrange,R.L.,&Ferraro,K.F.(1989).Assessingageandgenderdifferencesinperceivedrisk and fear of crime. Criminology 27 697-719. Lait,M.,&Glover,S.(2000,February15).Shootingscenesweredoctored,Perezsays. Los Angeles Times p. A1. Lane,J.(1998). Crimeandgangsinanurbansphere:Constructingthethreatandfearingthe future Unpublished doctoral dissertation, University of California, Irvine. Lewis,D.A.,&.Maxfield,M.G.(1980).Fearintheneighborhoods:Aninvestigationofthe impact of crime. Journal of Research in Crime and Delinquency 17 160-189. Liska,A.E.,Lawrence,J.J.,&Sanchirico,A.(1982).Fearofcrimeasasocialfact. Social Forces 60 760-770. Madriz,E.(1997). Nothingbadhappenstogoodgirls:Fearofcrimeinwomen’slives .Berkeley: University of California Press. Maxson,C.L.(1999).Ganghomicide:Areviewandextensionoftheliterature.InM.D.Smith& M.A.Zahn(Eds.), Homicide:Asourcebookofsocialresearch (pp.239-254).Thousand Oaks, CA: Sage. Lane, Meeker / SUBCULTURAL DIVERSITY519

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McCoy,H.V.,Wooldredge,J.D.,Cullen,F.T.,Dubeck,P.J.,&.Browning,S.L.(1996).Life stylesoftheoldandnotsofearful:Lifesituationandolderpersons’fearofcrime. Journalof Criminal Justice 24 191-205. Merry,S.E.(1981). Urbandanger:Lifeinaneighborhoodofstrangers .Philadelphia:Temple University Press. Miethe,T.D.(1995).Fearandwithdrawalfromurbanlife. TheAnnalsoftheAmericanAcademy of Political and Social Science 539 14-27. Moore,J.W.(1978). Homeboys:Gangs,drugs,andprisoninthebarriosofLosAngeles .Phila delphia: Temple University Press. Moore,J.W.,Vigil,D.,&Garcia,R.(1983).ResidenceandterritorialityinChicanogangs. Social Problems 31 182-194. OrangeCountyChiefs’andSheriff’sAssociation(OCCSA).(1997). OrangeCounty’sgang strategy Santa Ana, CA: Author. OrangeCountyChiefs’andSheriff’sAssociation(OCCSA).(1998). Thefinalreportofthe OrangeCountyconsortiumCOPSproject [GrantNumber96-CN-WX-0019].Submittedto the United States Department of Justice, Office of Community Oriented Policing. Peterson,J.(1997,February20).Clintonunveilsproposalstofightjuvenileviolence. Los Angeles Times, Orange County Edition p. A8. Rountree,P.W.(1998).Areexaminationofthecrime-fearlinkage. JournalofResearchinCrime and Delinquency 35 341-372. Rountree,P.W.,&.Land,K.C.(1996).Perceivedriskversusfearofcrime:Empiricalevidence of conceptually distinct relations in survey data. Social Forces 4 1353-1376. Saavedra,T.(1992,September19).Robberies:OClargelyescapesurbanepidemicofcarjacking casesbut2fatalattackslocallydemonstrateareanotimmune. TheOrangeCountyRegister p. B6. Saavedra,T.(1993,October20).Vilegesturepossiblecauseofrodattack. TheOrangeCounty Register p. A5. Sacco,V.F.(1998).Mediaconstructionsofcrime.InG.W.Potter&V.E.Kappler(Eds.), Constructingcrime:Perspectivesonmakingnewsandsocialproblems (pp.37-52).Prospect Heights, IL: Waveland Press. Sampson,R.J.,&Groves,W.B.(1989).Communitystructureandcrime:Testingsocialdisorga nization theory. American Journal of Sociology 94 774-802. Samspon,R.J.,Raudenbush,S.W.,&Earls,F.(1997,August15).Neighborhoodsandviolent crime: A multilevel study of collective efficacy. Science 277 918-924. Shaw,C.R.,&McKay,H.D.(1942). Juveniledelinquencyandurbanareas .Chicago:Univer sity of Chicago Press. Skogan,W.G.(1977).PublicpolicyandthefearofcrimeinlargeAmericancities.InJ.A.Gardi ner (Ed.), Public law and public policy (pp. 1-17). New York: Praeger. Skogan,W.G.(1990). Disorderanddecline:Crimeandthespiraldecayofurbanneighbor hoods New York: Free Press. Skogan,W.G.(1995).CrimeandtheracialfearsofWhiteAmericans. AnnalsoftheAmerican Academy of Political and Social Science 539 59-71. Skogan,W.G.,&.Maxfield,M.G.(1981). Copingwithcrime:Individualandneighborhood reactions Beverly Hills, CA: Sage. Spergel,I.A.(1995). Theyouthgangproblem:Acommunityapproach .NewYork:OxfordUni versity Press. Stafford,M.C.,&Galle,O.R.(1984).Victimizationrates,exposuretorisk,andfearofcrime. Criminology 22 173-185. 520CRIME & DELINQUENCY / OCTOBER 2000

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Stanko,E.A.(1995).Women,crime,andfear. AnnalsoftheAmericanAcademyofPoliticaland Social Science 539 46-58. St.John,C.,&Heald-Moore,T.(1996).Racialprejudiceandfearofcriminalvictimizationby strangers in public settings. Sociological Inquiry 66 267-284. Taylor,R.B.,&Covington,J.(1993).Communitystructuralchangeandfearofcrime. Social Problems 40 374-395. Taylor,R.B.,Gottfredson,S.D.,&Brower,S.(1985).Attachmenttoplace:Discriminantvalid ity,andimpactsofdisorderanddiversity. AmericanJournalofCommunityPsychology 13 525-542. Taylor,R.B.,&Hale,M.(1986).Testingalternativemodelsoffearofcrime. JournalofCriminal Law & Criminology 77 151-189. Tyler,T.R.(1980).Impactofdirectlyandindirectlyexperiencedevents:Theoriginof crime-relatedjudgmentsandbehaviors. JournalofPersonalityandSocialPsychology 39 13-28. U.S.BureauoftheCensus.(1994). Countyandcitydatabook:1994 .Washington,DC:Govern ment Printing Office. Vigil,J.D.(1988). Barriogangs:StreetlifeandidentityinSouthernCalifornia .Austin:Univer sity of Texas Press. Vila,B.,&Meeker,J.W.(1997).Aregionalgangincidenttrackingsystem. JournalofGang Research 4 23-26. Warr, M. (1985). Fear of rape among urban women. Social Problems 32 238-250. Warr,M.(1994).Publicperceptionsandreactionstoviolentoffendingandvictimization.InA.J. Reiss&J.A.Roth(Eds.), Understandingandpreventingviolence:Consequencesandcontrol (Vol 4, pp. 1-66). Washington, DC: National Academy Press. Will,J.A.,&McGrath,J.H.(1995).Crime,neighborhoodperceptions,andtheunderclass:The relationshipbetweenfearofcrimeandclassposition. JournalofCriminalJustice 23 163-176. Wilson,J.Q.,&.Kelling,G.L.(1982,March).Brokenwindows:Thepoliceandneighborhood safety. The Atlantic Monthly 249 29-38. Yin, P. (1985). Victimization and the aged Springfield, IL: Charles C Thomas. Lane, Meeker / SUBCULTURAL DIVERSITY521



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1 EXAMINING THE LINK BETWEEN OFFENDING, THE NEIGHBORHOOD CONTEXT, AND FEAR OF CRIME AMONG PROBATIONERS By KATHERYN G. ZAMBRANA A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT O F THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS UNIVERSITY OF FLORIDA 2012

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2 2012 Katheryn G. Zambrana

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3 To my mother and father, Anna and Jay Zambrana

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4 ACKNOWLEDGMENTS I would like to first thank my thesis committee. Thank you to my c hair, Dr. Jodi Lane, who has supported me and encouraged me throughout this project. Dr. Lane has been a truly great advisor and I feel that I have gained so many valuable lessons that I will carry with me throughout my graduate and professional career. I have grown and learned so much working with her, both personally and academically; I am so thankful for her and grateful to have her as my mentor. I am very thankful for my committee members, Dr. Lonn Lanza Kaduce and Dr. Ronald Akers. The time, support, a nd assistance they have given me has been invaluable and was integral to my project and I owe them so much thanks. I feel so lucky to have a committee of faculty who not only were truly exceptional, but always were willing to provide any support or guidanc e I needed. This project would not have been possible without them. I would like to also thank Saskia Santos. This project would not have been possible without her. Saskia has not only been a great friend but a wonderful graduate mentor. I have learned so much from her. Her constant encouragement and motivation throughout this project meant so much. She is a truly exceptional person who is always think I could have ask ed for a better colleague and friend to work with. I am very thankful to the Alachua County Court Services Misdemeanant Probation for allowing us to work with them on this project and collect data. I would like to express my gratitude to them and especial ly thank Ms. Cindy Morton (Former Director of Court Services) and Ms. Sharon Longworth (Probation Program Supervisor) for allowing us to obtain access to their agency. I would also like to thank Tom Tonkavich, who constantly supported us in the endeavor (D irector of Court Services). I

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5 would also like to give a special thanks to the probation officers who worked with us in conducting research, without their efforts we would have not been able to collect our data and reach so many participants. Thank you to t he probation staff: Wanda Mayberry, Kris Anderson, Dana Patterson, Valarie Green, Drew Gallaugher, Amanda Mash, Willfredo Melendez, Rodney Williams, Margie Nunez, and Nicole Wise. I would also like to give a special thanks to probation staff, specifically Bruce, who constantly worked with us to obtain criminal histories and Melanese who helped us recruit participants during the study. I would like to also thank all of the research assistants who helped me conduct interviews, enter data, and transcribe int erviews. Their help was so incredibly valuable and were integral to this project. Thank you to Colin Murphy, Joseph Dimaio, Mark Villa, Jacob Whitney, Ervin Goad, Jennifer Harrington, Griffin Peters, and Jennifer Lee. There work, time, and effort in this p roject meant so much. I felt truly lucky to have had the opportunity to work with such great research assistants. I would also like to give a very special thank you to Ashley Price. Before beginning graduate school, being her ambitious self, Ashley helped Saskia and I collect data by conducting interviews with us. There are not enough great ways to express how wonderful it was to work with her. She was constantly there to assist and support us thorough this project. I am so thankful for all of her help and hope that I can extend the same back to her. She is an amazing student, colleague, and friend. I would like to thank my family. Thank you to my mother, Anna, my father Jay, and my sister, Cristy. I feel so blessed to have been lucky enough to have paren t like them. They have given me constant love, encouragement, and support. They believed

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6 in me every step of the way and believed in me when I did not. I would like to give a special thanks to my father, who was always there for me and encouraged me every step through this project, graduate school, and life. I will miss him so much.

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7 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 10 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 14 2 LITERATURE REVIEW ................................ ................................ .......................... 18 Fear of Crime: An Overview ................................ ................................ .................... 18 Fear and Social Disorganization ................................ ................................ ............. 19 The Link between Fear and The Neighborhood ................................ ............... 22 Disorder ................................ ................................ ................................ ..... 23 Community concern ................................ ................................ ................... 23 Subcultura l diversity ................................ ................................ ................... 24 The Neighborhood and Fear among Offenders ................................ ................ 25 Personal Fear of Crime ................................ ................................ ........................... 26 Demographic Predictors ................................ ................................ ................... 26 Personal Fear of Crime among Offenders ................................ ........................ 27 Precautionary Behaviors: Responses to Pers onal Fear of Crime ..................... 29 Altruistic Fear of Crime ................................ ................................ ........................... 31 Demographic Predictors ................................ ................................ ................... 31 Altruistic Fear of Crime among Offenders ................................ ........................ 33 Precautionary Behaviors: Responses to Altruistic Fear of Crime ..................... 33 Measur ing Fear of Crime: Offense types and fear ................................ .................. 34 3 RESEARCH METHODOLOGY ................................ ................................ ............... 36 Personal Fear of Crime and Offending ................................ ................................ ... 36 Research Question 1 ................................ ................................ ........................ 36 Hypothesis 1 ................................ ................................ ................................ ..... 36 Personal Fear of Crime and Social Disorganizat ion ................................ ............... 36 Research Question 2 ................................ ................................ ........................ 36 Hypothesis 2 ................................ ................................ ................................ ..... 37 Personal Fear of Crim e and Precautionary Behaviors ................................ ............ 37 Research Question 3 ................................ ................................ ........................ 37 Hypothesis 3 ................................ ................................ ................................ ..... 37 Altruistic Fear of Crime and Offending ................................ ................................ .... 38 Research Question 4 ................................ ................................ ........................ 38 Hypothesis 4 ................................ ................................ ................................ ..... 38 Research Design ................................ ................................ ................................ .... 39

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8 Research Setting ................................ ................................ .............................. 39 Population and Sample Selection ................................ ................................ ..... 39 Population and Sample Selection (Random Sample) ................................ ....... 40 Population/Sample Selection (Convenience Sample) ................................ ...... 42 R esponse Rate ................................ ................................ ................................ 43 Recruiting Participants: Procedure ................................ ................................ ... 45 Participant Benefits ................................ ................................ .......................... 48 Setting up Interviews ................................ ................................ ........................ 49 Official Records Data Procedure ................................ ................................ ...... 51 Semi Structured Interviews Procedure ................................ ............................. 53 Interview Variables to be used in this Study ................................ ........................... 57 Operationalization/ Measures ................................ ................................ ........... 57 Dependent Variables ................................ ................................ ........................ 57 Fear of crime ................................ ................................ .............................. 58 Altruistic fear ................................ ................................ .............................. 60 Prec autionary behaviors ................................ ................................ ............ 62 Independent Variables ................................ ................................ ..................... 63 Offense history ................................ ................................ ........................... 63 Social disorganization ................................ ................................ ................ 66 Demographic Variables ................................ ................................ .................... 68 Qualitative Variables ................................ ................................ ........................ 69 Fear of crime ................................ ................................ .............................. 70 Altruistic fear of crime ................................ ................................ ................ 70 Precautionary behaviors ................................ ................................ ............ 70 Neighborhood perceptions ................................ ................................ ......... 71 Analytic Plan ................................ ................................ ................................ ........... 71 4 RESULTS ................................ ................................ ................................ ............... 83 Descriptive Statistics ................................ ................................ ............................... 83 Independent Variables: ................................ ................................ .................... 83 Participant characteristics ................................ ................................ .......... 83 Official criminal history ................................ ................................ ............... 85 Self report criminal history ................................ ................................ ......... 87 Social disorganization ................................ ................................ ................ 88 Dependent Variables: ................................ ................................ ....................... 89 Fear of crime ................................ ................................ .............................. 89 Altruistic fear ................................ ................................ .............................. 90 Precautionary behaviors ................................ ................................ ............ 94 Quantitative and Qualitative Data Analysis Findings ................................ .............. 94 Personal Fear of Crime ................................ ................................ .................... 95 Research question 1 and 2 ................................ ................................ ........ 95 Predicting general fear of crime ................................ ................................ 95 Predicting fear of violent crime ................................ ................................ 100 Predicting fear of property crime ................................ .............................. 103 Predicting fear of drug crime ................................ ................................ .... 106 Summary of Findings for Personal Fear of Crime ................................ .......... 109

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9 Precautionary Behaviors ................................ ................................ ................ 111 Research question 3: ................................ ................................ ............... 111 Predicting defensive precautionary behaviors ................................ .......... 112 Predicting avoidance precauti onary behaviors ................................ ......... 115 Predicting target hardening precautionary behaviors ............................... 119 Summary of Findings for Precautionary Behaviors ................................ ........ 120 Qualitative Data Analysis Findings ................................ ................................ ....... 122 Personal Fear of Crime and Offending ................................ ........................... 123 Qualitative findings ................................ ................................ ................... 123 Altruistic fear of crime and offending ................................ ........................ 126 Precautionary Behaviors and Offending ................................ ......................... 128 Qualitative findings ................................ ................................ ................... 128 Fear of crime and social disorganization ................................ .................. 130 5 DISC USSION AND CONCLUSION ................................ ................................ ...... 152 Summary of Findings ................................ ................................ ............................ 152 Quantitative Finding ................................ ................................ ....................... 152 Qualitative Findings ................................ ................................ ........................ 158 Study Limitations and Suggestions For Future Research .............................. 160 Study implications ................................ ................................ .......................... 163 APPENDIX A COURT SERVICES APPROVAL ................................ ................................ .......... 165 B IRB APPROVAL ................................ ................................ ................................ ... 167 C LETTER SENT TO PROBATIONERS ................................ ................................ .. 168 D REVISED LETTER TO PROBATIONERS ................................ ............................ 169 E PARTICIPANT BENEFITS APPROVAL ................................ ............................... 170 F CRIMINAL HISTORY FORM ................................ ................................ ................ 172 G INFORMED CONSENT ................................ ................................ ........................ 177 H SURVEY INSTRUMENT ................................ ................................ ....................... 179 I OFFENSE CATEGORIES USED BY ALACHUA COUNtY PROBATION ............. 203 LIST OF REFERENCES ................................ ................................ ............................. 205 BIOGRAPHIC AL SKETCH ................................ ................................ .......................... 211

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10 LIST OF TABLES Table page 3 1 Full Sample Overview of All Participants (Non Interviewed/Interviewed Participants). ................................ ................................ ................................ ....... 74 3 2 Fear of crime Factor Analysis: Factor 1 Loadings and Reliability Test. ................ 75 3 3 Precautionary Behavior Factor Analyses: Factor Loadings1 and Re liability Test. ................................ ................................ ................................ ................... 76 3 4 Physical and Social Disorder Factor Analysis: Factor Loadings and Reliability Test. ................................ ................................ ................................ ................... 77 3 5 Collective Eff icacy Factor Analysis: Factor Loadings and Reliability Test. ......... 77 3 6 Fear of Crime and Offending Research Questions. ................................ ............ 78 3 7 Fear of Crime and Coping Mechanisms. ................................ ............................ 80 3 8 Fear of Crime and Social Disorganization. ................................ ......................... 81 3 9 Personal Fear of Crime Step Wise OLS Reg ression Overview: Predicting General, Violent, Property, and Drug Fear of Crime. 1 ................................ ........ 82 4 1 Interviewed Sample: Sample Characteristics (original & convenience sample). ................................ ................................ ................................ ............ 134 4 2 Interviewed Sample: Current Offense Characteristics (original & convenience sample). ................................ ................................ ................................ ............ 136 4 3 Interviewed Sample: Official Prior Criminal History (o riginal & convenience sample). ................................ ................................ ................................ ............ 137 4 4 Official Criminal History Measures Descriptive Statistics. ................................ 137 4 5 Interviewed Sample: Se lf Report Criminal History (original & convenience sample). ................................ ................................ ................................ ............ 138 4 6 Social Disorganization Descriptive Statistics. ................................ ................... 138 4 7 Fear of Crime Descriptive Statistics. ................................ ................................ 138 4 8 Fear of Crime Descriptive Statistics (for each item). ................................ ......... 139 4 9 Fear of Crime Frequencies (for each item) N=202. ................................ .......... 139 4 10 Altruistic Fear of Crime Descriptive Statistics. ................................ .................. 140

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11 4 11 Altruistic Fear of Crime Frequencies. ................................ ............................... 140 4 12 Precautionary Behaviors Descriptive Statistics. ................................ ................ 140 4 13 Precautionary Behaviors Descriptive Statistics (for each item ) N=202. ............ 141 4 14 OLS Regression Predicting General Fear of Crime. ................................ ......... 142 4 15 OLS Regression Predicting Fear of Violent Crime. ................................ ........... 143 4 16 OLS Regression Predicting Fear of Property Crime. ................................ ........ 144 4 17 OLS Regression Predicting Fear of Drug Crime. ................................ .............. 145 4 18 Logistic Regression Predicting Use of Defensive Precautionary Behaviors. .... 146 4 19 Logistic Regression Predicting Use of Avoidance Precau tionary Behaviors. ... 147 4 20 Logistic Regression Predicting Use of Target Hardening Precautionary Behaviors. ................................ ................................ ................................ ........ 148 4 21 Fear and Of fending Themes (types of crimes). ................................ ................ 149 4 22 Altruistic Fear Themes (fear of family). ................................ ............................. 150 4 23 Precautionary Behaviors Themes. ................................ ................................ .... 150 4 24 Neighborhood Perceptions Themes. ................................ ................................ 151

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12 Abstract o f Thesis Presented to t he Graduat e School of the University o f Florida in Partial Fulfill ment of the Requirements for the Degree o f Master o f Arts EXAMINING THE LINK BETWEEN OFFENDING, THE NEIGHBORHOOD CONTEXT, AND FEAR OF CRIME AMONG PROBATIONERS By Katheryn Zambrana May 2012 Chair: Jodi Lane Major: Criminology, Law and Society There h as been much research on fear of crime and understanding what affects offending populations, specifically among probationers. Due to the large representation of probationers in the correctional population, further analysis of this group is important. The present study is the first to examine fear of crime among adult probationers, specifically looking at the relationship between the crimes offenders commit and the crimes they are fearful of, how offending affects altruistic fear, what steps offenders take to cope with crime, and what effect the neighborhood context has on fear of crime and offending The present study uses data collected from 202 semi structured interviews with misdemeanant probationers to examine the role that offending plays on fear of crime. Quantitative and qualitative findings were analyzed. Results show that female and non white offenders are fearful of crime. Findings also show that seriousness of ffending does not affect one s fear of crime. history and current offense were found to be important predictors of fear. Certain neighborhood factors were found to be important in predicting personal fear of crime.

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13 Findings on precautionary behaviors are less evident. Altruistic fear was found to be present among some offenders.

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14 CHAPTER 1 INTRODUCTION Fear of crime has been an issue of great importance in the political arena for several years. Policymakers have worked to make communities feel safer by enacting tougher criminal laws. However, it is unclear if such laws have had a positive impact on began to receive attention by both researc hers and alike (Ferraro, 1996; Maxfield, 1984). Scholars have noted that fear of crime has a greater impact on Law Enforcement and Administration of Justi consequences and behaviors (Wyant, 2008). Additionally, fear of crime is argued to be elevated in those populations who liv e and spend time in areas where crime and victimization is prevalent (Lane, 2009). More specifically, those who engage in criminal behaviors are not only more likely to be victimized (by surrounding themselves with other offenders) but may have higher leve ls of fear, because of their involvement in crime (Lane, 2009). As fear of crime continues to affect communities in the United States, it becomes imperative to study not only on non offenders, as past research has traditionally focused on, but to examine t hose populations that are most often exposed to crime especially offending populations (Lane & Fox, forthcoming). There have been only a handful of studies that have examined fear of crime among offenders (Lane, 2006; Lane, 2009, May, 2001; Lane & Fox, forthcoming; May, Vartanian, & Virgo, 2002). Based on past research on fear of crime, it can be argued

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15 (Lane, 2009). If offenders are fearful of certain crimes, they may take part in additional criminal activity in an effort to reduce their fear, or they may stay away from specific environments (e.g. certain neighborhoods) because of that fear (Lane, 2009). It is possible that the crimes that offenders commit can have a c onsiderable effect on their levels is crucial and may allow us to gain a more complete view on fear of crime. Moreover, probationers represent a critical offender popula tion to study. Probationers have not been studied as extensively as other offending populations (Petersilia, 1997). As of 2008, there were an estimated 5.1 million individuals on community supervision in the United States (Bureau of Justice Statistics, 200 9). Probation is a correctional population that is often overlooked and yet is closest to the non offending community in terms of their environment. The correctional population as a whole is comprised of offenders who are sanctioned to jail, prison, or co mmunity supervision (Glaze & Bonczar, 2009). Community supervision includes adults on probation or parole and makes up 70% of the correctional population. Specifically, of those placed on community supervision, 4,270,917 (or 84%) of individuals are sentenc ed to probation, a much greater percent, compared to those on parole (16%) (Glaze & Bonczar, 2009). Roughly 52% of probationers are re incarcerated within 3 years of their release from probation (Langan & Levin, 2002). Due to the fact that probation terms are completed in the community, the courts have minimal control over what probationers encounter daily. There may be elements in the community, which could affect their fear of crime and possibly their ability to successfully complete their probation (Lan e, 2009). Understanding the influence that

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16 probation would provide an effective way of addressing influences that lead to recidivism and/or violations of probation. If pr obationers, because of their participation in crime, are worried about being victimized or about their families being victimized, they may then be more likely to associate with negative peers (e.g., gang members) or carry weapons (Lane, 2006; Lane, 2009). Taking part in these behaviors might result in a violation of their probation and increase the likelihood that such weapons will be used in the commission of a crime or new law violation. This study will contribute to the existing body of knowledge on thr ee primary ways: First, the study will add to the limited amount of research on fear of crime among probationers and offenders overall. The few studies that have been done on offenders have been mostly focused on juvenile populations. Addressing adult off enders is imperative to gaining a comprehensive understanding of fear, as it applies to adults, and this study will serve as a vehicle to extend the theoretical framework on fear as it applies to adult probationers. Second, the correctional population tod ay is mostly comprised of individuals sentenced to probation, so this study will add to the sparse literature on the largest group of offenders under correctional supervision. Third, the present study will also contribute to the literature methodologically by using semi structured interviews, with both quantitative and qualitative measures. This study will accomplish the proposed items by examining the following research ? (2)

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17 levels for themselves and for their families? (4) How do probatio ners cope with fear of crime?

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18 CHAPTER 2 LITERATURE REVIEW Fear of Crime: An Overview emotional res ponse of dread or anxiety to crime or symbols that a person associates of physical dan ger or vulnerable to some type of harm to their property or person based on their environment (Fisher & May, 2009). Fear can be shaped by individual perceptions of crime and vulnerability to victimization, which is often influenced by outside experiences (Ferraro, 1995). However, when studying fear, it is crucial to make a distinction between thoughts abo ut their likelihood of victimization (Ferraro, 1995, 1996; Stafford & Galle, 1984; Warr, 1984, 1990; Warr & Stafford, 1983), has be e n described as being a study in 1971, were the differences between perceived risk and fear brought to light on their likelihood of being victimized (Ferraro, 1995; Wyant, 2008). So if one believes that he or she is likely to be a victim of crime in general, it does not necessarily imply that the individual will be fearful of crime (LaGrange & Ferraro, 1989; Wyant, 2008). These perceptions of risk and fear are often nested in the contextual framework of the

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19 co mmunity or environment an individual lives (that lead to varying levels of fear) (Skogan, 1990; Covington & Taylor, 1991; Taylor & Hale, 1986; Wyant, 2008). Fear and Social Disorganization Fear of crime can be studied on a micro and macro level. Most of the seminal work on fear of crime has taken a micro level approach. Recently, many have recognized the importance of contextual factors in predicting fear of crime, in particular special focus has been placed on examining perceptions of the neighborhood on e lives in and the physical incivilities around them to examine its influence on fear. The present study will look at both individual level predictors and neighborhood level predictors of fear, as perceived by the offenders themselves. Social Disorganizat ion takes an ecological perspective, focusing on characteristics focus on individual level factors that lead to crime or fear (Markowitz, et al., 2001; Shaw & McKay, community to realize the common values of its residents and maintain effective social Meeker 2003). As such, social disorganization places focus on the community one lives in and examines structural factors like the lack of solidarity among neighbors, community cohesion, and integration (Kubrin, et al., 2009). Weakened social controls, such as weak bonds among neighbors, rapid urbanization, and the erosion of traditional value systems replaced by criminal values or minimal interactions among neighbors often lead to disorganized neighborhoods (Shaw & McKay, 1942, 1969; Bursik & Grasmick, 1993; S ampson & Groves, 1989). According to Shaw and McKay (1942) disorganization can often be produced by three factors: 1)

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20 racial and ethnic heterogeneity, or communities that are racially or ethnically diverse; 2) high residential mobility, where residents ar e often moving in and out; and 3) poverty, areas of low socio economic status (Shaw & McKay, 1942). Essentially, the underlying framework of the theory argues that when a neighborhood or community is unable to preserve effective social controls or maintain commonly shared values, a neighborhood becomes disorganized and there is an increased likelihood for crime to occur (Kubrin, Stucky, & Krohn, 2009; Lane & Meeker, 2004; Shaw & McKay, 1942). When informal social controls are present in a neighborhood, mem bers of that community are more likely to share a common goal to keep their community safe and engage in efforts to reduce or prevent crime (Kornhauser, 1978). Disorganized neighborhoods, especially those experiencing rapid urbanization, lack these key cha racteristics, fostering an environment that is conducive to criminality. With respect to fear of crime, a disorganized neighborhood that prevents community members from establishing ties and has high residential mobility and racial heterogeneity, also con (Covington & Taylor, 1991; DuBow, McCabe, and Kaplan, 1979, Maxfield, 1987b), fear of crime is higher in areas that are disorganized, and have more crime (Covington & Taylor, 1991). Social disorganization has been measured in various ways. Although neighborhood elements, like poverty and ethnic heterogeneity, create a community condition that allows for community disorgan ization to occur, they are only indirect measures of crime (Sampson, et al., 1997). Extending on the work of Shaw & McKay,

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21 Sampson & Groves (1989) used data from the 1982 British Crime Survey to locate more appropriate measures of social disorganization a nd found consistent findings with their previous research. In their study, Sampson and Groves noted the importance of capturing social networks, which are a regarded as an essential structural element in the social disorganization framework. Here they pro posed a causal model that included five community level variables that are thought to be causes of social disorganization, including urbanization, ethnic heterogeneity, low socio economic status (SES), residential mobility, and family disruption (Sampson & Groves, 1989; Shaw & McKay, 1979; Sampson, 1987). More specifically, they recognized exogenous variables (e.g. poverty/SES, urbanization, stability, and heterogeneity) and introduced family disruption as an exogenous variable as well (Sampson & Groves, 1 989). Also, they added intervening measures of social disorganization that included social networks between local community members, informal social control, and collective efficacy (Lowenkamp, Cullen, & Pratt, 2003; Sampson & Groves, 1989). They specifie d three key components as intervening variables that contribute to community decline and social disorganization: 1) limited local friendship networks (Skogan argues that when such networks are present community members are better able to protect their inte rests), 2) unsupervised youth peer groups (i.e. gangs), and 3) formal and informal organizational participation is low (this reflects a communities inability to form community solidarity) (Sampson & Groves, 1989). The work of Sampson, Raudenbush, & Earls (1997) highlighted the importance of collective efficacy in neighborhoods. They argued collective efficacy as a key element in neighborhood organization, noting that if communities have high levels of collective

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22 efficacy (including social ties, community c ohesion and informal controls), there would be a reduction in the amount of poverty and residential mobility, allowing for a lower levels of crime as a whole (Kurbrin, et al, 2009; Sampson, Raudenbush, & Early, 1997). Sampson & Raudenbush (2001) readdres sed the construct of disorder and documented the importance of social and physical disorder on a community, especially they used measures of physical disorder, social disor der, collective efficacy, and neighborhood characteristics (used in part in the Project of Human Development in Chicago Neighborhoods). They measured physical disorder by the amount of trash and graffiti that was present in the communities, and social dis order was measured by the amount of people who drank in public or sold drugs; collective efficacy was measured by asking if neighbors could trust one another or help each other; finally, neighborhood level characteristics were measured by the amount of pov erty or residential mobility present in such communities (Sampson & Raudenbush, 2001). Specifically, they found collective efficacy to be most predictive of future crime, so those communities that have low collective efficacy also had higher levels of viol ence and disorder (Sampson & Raudenbush, 2001). In an effort to build and extend the work on social disorganization, the present study will use subjective measures, that are similar to those used by Sampson and Raudenbush, to examine social disorganizati on as it relates to fear of crime. The Link b etween Fear a nd The Neighborhood Research on fear of crime has examined the impact of neighborhood factors on predicting fear of crime. It is argued that as social controls are weakened within neighborhoods, co mmunities often risk becoming more dangerous for community

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23 Convington & Taylor (1991) and Lane & Meeker (2003) have shown how a theoretical explanation (through social disorganizat ion) can help us better understand fear of crime. Three important neighborhood level models that have been used in much of the fear of crime literature include disorder, community concern, and subcultural diversity (Lane & Meeker, 2000, 2004; Maxfield, 198 4). Disorder The relationship between fear of crime and perceived disorder has been well established in the literature (Gates & Rohe, 1987; Lagrange, Ferraro, & Supancic, 1992; Skogan & Maxfield, 1981). The argument here is that when physical and social disorder is perceived in a community, it contributes to the amount of crime one perceives in his Sometimes such elements of disorder can be just as or more likely to pro duce fear among individuals as crime itself, as disorder can often lead to a sense of vulnerability among individuals (LaGrange et al., 1992; Rountree, 1998). In fact, people who live in areas that have high levels of social and physical disorder usually i ndicate having levels of fear that are not consistent with the actual level of crime in the community (i.e. fear levels are not usually consistent with the amount of crime in a neighborhood) (Gibson, Zhao, Lovrich, & Gaffney, 2002; Skogan, 1986). As such, when individuals report seeing more signs of incivilities or crime as an issue, they usually also report more fear of crime (Maxfield, 1984). Community c oncern The community concern perspective takes a comprehensive look at neighborhood perceptions and i s argued to be predictive of fear of crime (Taylor & Hale, 1986). The

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24 so does fear of crime (Taylor & Hale, 1986). So those who report to be more dissatisfied with their c ommunity or live in areas that have weak neighborhood social controls and social ties (including the lack of norms and values shared throughout the community) will have a greater likelihood of being fearful of crime (Snell, 2001; Taylor & Hale, 1986; Wyant 2008). Subcultural d iversity The concept of subcultural diversity is centered on the idea that individuals, especially those who have a reduced likelihood of being victimized, fear crime because they do not understand other people in their community wh o are racially and culturally different (Covington & Taylor, 1991; Lane & Meeker, 2000; Merry, 1981). In neighborhoods where residents are ethnically or racially diverse, it is difficult to build unity or cohesion among each other, due to their lack of un customs or culture (Lane & Meeker, 2000; Merry, 1981). The differences between community members can lead to fear due to the level of insecurity they have in the neighborhood they live in (Lane & Meeker, 2000). The construct of sub cultural diversity is still developing and has been regarded as being closely related to the concept of ethnic and racial heterogeneity. Yet, much research has found significant empirical support for the concept of subcultural diversity as a predictor of fear. Covington and Taylor (1991) found support for the diversity model in their analysis of 1,622 Baltimore residents living in multi cultural housing areas. Here they found that those who were more racially and culturally different from their neighbors reported higher levels of fear (Covington & Taylor, 1991). Findings in a later study by Lane & Meeker (2000) support the argument that diversity is related to fear. In their analysis of fear of crime and fear of

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25 gangs they asked 1,223 individuals how much they worry over problems with racial and ethnic relations. They found concern over diversity to be a strong predictor of fear and an even stronger predictor of fear of gangs (Lane & Meeker, 2000). The Neighborhood and Fear a mong Offenders Few studies ha ve examined the effects of neighborhood factors on fear of crime among adult offenders (Lane, 2009; May, 2001; May, Vartanian & Virgo, 2002). Of one study found that young o ffenders did not see factors associated with social disorganization in their communities (Lane, 2009); however, other research has found that those offenders who had increased perceptions of disorder in their neighborhoods had a tendency to be more fearful of crime (May, et. al., 2002). Perceived disorder has also been found to have an effect on the types of behaviors offenders take part in to protect themselves (May, 2001; Lane, 2009). Similarly, there has been mixed findings on the effects of collective efficacy on fear of crime. Gibson, et al. (2002) notes that there is still a limited amount of research exploring the relationship between collective efficacy and fear of crime (others include Lane & Fox, forthcoming). Interestingly, there have been mixed findings, some studies have found that higher levels of perceived collective efficacy lead to lower levels of fear (Gibson, et al., 2002); however, other studies (especially those on offending populations) have noted the inverse relationship present betwee n collective efficacy and fear (Lane & Fox, forthcoming). In an effort to increase the amount of research on neighborhood level factors and fear of crime, the neighborhoo d perceptions.

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26 Personal Fear of Crime Demographic Predictors In addition to perceived neighborhood characteristics, it is also essential to examine individual predictors of fear. There are several different individual level economic status, and health (Ferraro, 1995; Rader, May, & Goodrum, 2007; Warr, 1994). With respect to the relationship between gender and fear, findings show that women are consistently more afraid t han men, even though they are less likely to be victimized (Fisher & May, 2009). Females, especially, white females, tend to be more perceptions of the effects of crime vic timization (Fisher & May, 2009; Rader et al., 2007; environmental cues, in that females may tend to focus on issues such as the number of people present or the lack of police in the area, while males think about their physicality and ability to get out of a situation (Fisher & May, 2009). Moreover, researchers have been examining the link between fear and age for several years. Early research found that the elderly were more fear ful than younger individuals tend to be more afraid of crime and also have a higher risk of being victimized (Ferraro, 1996; Ferraro & Lagrange, 1992; Lane & Meeker, 2000; Ra der, May, & Goodrum; Roundtree, 1998; Warr, 1994). Some have argued, however, that the inconsistencies in findings of fear among the elderly may vary and be correlated to the types of techniques they engage in to protect themselves (Lane & Meeker, 2000).

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27 Findings on the effects of race on fear are inconsistent. Some studies have shown that whites tend to be more fearful, but most results show that non whites are more afraid (Lane & Meeker, 2003; Rader, et al., 2007; Skogan, 1995). Moreover, some studies ha neighborhood and that racial diversity is related to greater fear of crime (Rader, et al., 2007). With regards to income, those who live in low SES areas tend to indicate higher leve ls of fear than those in other areas (Rader, et. al., 2007). This can be the result of living in areas that have higher amounts of disorder present. Overall, however, the literature has notes that fear levels have a tendency to be lower among white males w ho are from a higher socio economic background (Lane & Meeker, 2000). Personal Fear of Crime among Offenders As mentioned earlier, fear of crime research has generally looked at the general 2003). Of the studies that have been conducted on offenders, they have primarily focused on juvenile delinquents, rather than adult offenders. The limited amount of research on offenders can be due to several reasons. One study by Lane (2009) examines fea r of crime among juvenile offenders, notes this could be due to not expecting those who engage in crime (or induce fear on others) to be fearful themselves. The research conducted on offending populations, specifically juvenile offenders generally have sh own low levels of fear (Lane, 2009). One study comparing male and female offenders, found no differences in fear levels (Lane, 2009). There has been only one published study that examined fear of crime among probationers, but it was among juveniles (Lane 2 006). One third of youths on probation were found to be afraid of

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28 serious offenses, such as being shot in the street, murdered or being a victim of a drive by. Furthermore, individuals who were less involved in crime were found to be more afraid of crime ( Lane, 2006). T he type of probation status was not predictive of fear (Lane, 2006). Those who had experienced some kind of victimization were found to be more fearful of burglary (Lane, 2006). Lane (2006, 2009), who has done studies on both incarcerated ju veniles and probationers, found that those who were incarcerated indicated less fear overall than those who are placed on probation. This could be due to the fact that probationers remain in the community, where they not only deal with criminality in their communities, but most often high levels of disorder and community decline. More studies, especially among adult probationers are needed to understand fear among offenders in the community. A recent study by Lane & Fox (forthcoming) is the first to look a t fear among an adult offending population. Based on the data collected on 2,414 jail inmates across the state of Florida, Lane & Fox (forthcoming) tested measures of crime specific fear (i.e. fear of property, personal and gang related crime). Their findi ngs indicated that inmates did not report high levels of fear and were generally more afraid of personal/violent crimes than any other type of crime (i.e. property and gang related crimes) (Lane & Fox, forthcoming). Additionally, other studies have noted that offenders have the possibility of becoming victims. Those who have a history of offending, have the chance of continued offending due to retaliation or due to offenders maintaining values that are consistent with taking part in violence or crime to de al with their victimization (Sampson & Lauritsen, 1990). Because offenders are around crime more often than non offenders,

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2 9 willing to report any victimization they expe rience) (Sampson & Lauritsen, 1990). Overall, more research on fear of crime among adult offenders is necessary so that we may better understand offenders fear levels and its effects on offending patterns. Precautionary Behaviors: Responses to Personal Fe ar of Crime There are several consequences to fear of crime. Many have noted how a behaviors (Conklin, 1975; Rader, May, & Goodrum, 2007; Ross, 1993; Wyant, 2008). More spe cifically, fear often results in individuals changing or restricting their behaviors by avoiding certain areas of their neighborhoods and consequently withdrawing from their community (Wyant, 2008). As such, fear of crime begins to influence an (Ferraro, 1995). haviors that individuals engage in, in an effort to cope with their fear, include defensive or avoidance measures (Ferraro, 1995; Rader, et al., 2007). Defensive responses are those that are proactive in nature and include behaviors like securing a gun or other weapon in their home or on their person, installing extra locks on their home or car, and adding outside lighting (Ferraro, 1995; Rader, et. al., 2007). Avoidance behaviors include staying away from certain areas during different times of the day and refraining from walking around certain areas or using public transportation (Ferraro, 1995; Rader, et. al., 2007; Skogan & Maxfield, 1981). In many situations individuals may combine both behavioral approaches in an effort to cope with their fear. Some p rotective

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30 measures that individuals may use include installing more locks, burglar alarms, carrying a whistle, or buying a watchdog (Gates & Rohe, 1987). Some might even take tch or other organizations that address crime prevention (Gates & Rohe, 1987). Moreover, certain demographic groups engage in different precautionary behaviors. Women, who tend to be more fearful but have a reduced likelihood of victimization, are likely t o engage in avoidance behaviors (women may also carry nonlethal objects like pepper spray) like avoiding areas they view to be dangerous (Ferraro, 1995). Men, on the other hand, have been found to be more likely to carry and own a gun (Ferraro, 1995; Wri ght 1991). Those who do carry a gun for self defense purposes are those have a high perception of risk of being victimized (Ferraro, 1995). National Polls asking about approaches taken when one is fearful of crime found that 27% of individuals tend to carr y a gun for protection (Rader, et al., 2007). This may hold among offenders who are fearful of crime, due to the fact that they already are immersed in crime as an element of their lifestyle. Studies among juvenile offenders have found that offenders who h ave friends that engage in delinquent behavior and perceive disorder or perceive a higher risk of victimization had a higher likelihood of carrying a weapon, such as a gun (May, 2001; Lane, 2009). In a study examining juvenile offenders, Lane (2009), found that male offenders were more likely to take part in defensive behaviors like carrying a weapon than female offenders, who were more likely to take part in avoidance behaviors. tyle. In fact, although individuals may make changes over time in response to the threat of

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31 victimization, these changes are often minimal (Ferraro, 1995). Moreover, such reactions are viewed to be a form of coping with one s fear of crime, and as such one neighborhood may have the possibility to affect not only fear but also the way that we cope with our fear. Ferraro (1995) notes that those who live in urban low SES offenders tend to pref er avoiding crime and situations where they perceive they may be victimized rather than taking defense measures (Ferraro, 1995). One would expect to find that offenders who are fearful of crime would take part in similar coping mechanisms, with variations among different demographic groups. Altruistic Fear of Crime Another important dimension of fear that is still developing in the literature is fear they are close to (altruistic fear) than they are for themselves (Madriz, 1997; Warr, (ren) can result in parents taking more precautions to protect their children from any harm or cr ime, than they do to protect themselves (Snedker, 2006; Warr & Ellison, 2000). This is due to strong ties and relationships built between family members (Warr & Elliison, 2000). However, as Warr & Elison (2000) argue, altruistic fear is complex and can var y, as some individuals may be more afraid for a child while others carry greater fear for a spouse. Even more complex are the variations of altruistic fear across demographic factors like gender. Demographic Predictors Males and females can experience al truistic fear differently. Females, specifically mothers, are argued to be likely to be more invested in the safety of their children and

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32 may have higher fear for them than fathers do (Warr & Ellison, 2000). This argument is premised on the idea that mothe rs spend more time around their children on a daily basis than fathers (Warr & Ellison, 2000). Males, however, can hold the same degree of fear for their children as they assume the protective role in a family (Kirkpatick, 1963). Interestingly, males have been found to be less fearful for themselves and more fearful for others (Warr & Ellison, 2000). An important piece by Warr and Ellison (2000) examined personal fear versus fear for others (including children and spouses) among married residents in Texas. They found that about 84% of the participants living in family households indicated concern or fear for at least one other person they live with (Warr & Ellison, 2000). More specifically, they found that 70% of their sample (of 1,006 respondents) indicated having concerns about the safety of another family member, indicated that they have personal fear of crime, many also indicated that they had some level of concern for their spouse (Warr & Ellison, 2000). Warr & Ellison found men tend to indicate fear for their wives more often (47%) than women for their husbands (33%). Such concern decreases with age. Overall, however, husbands tend to be more fearful for their wives ( i.e. display greater spousal fear) (Warr & Ellison, 2000). child revealed interesting variations based on age and sex of the child. Warr & Ellison (2000) found that generally parents are more fearful for their children when they are younger, and as children and their parents get older that fear decreases. Parents fear for female children t ends to be greater than fear for male children overtime (Warr &

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33 Ellison, 2000). Increased fear levels for female children over male children are most evident when the child is between the ages of 6 and 10 and then again after the age of 16. Also, they fou nd women to indicate greater concern for their children (Warr & Ellison, 2000). Altruistic Fear of Crime among Offenders To date, there has not been an analysis of altruistic fear among offending populations, an examination of the relationship between pe rsonal fear versus fear for others among offenders may reveal some interesting relationships, particularly because family members. Ferraro (1995) points out that when individuals try to avoid or protect be paramount Precautionary Behaviors: Responses to Altruistic Fear of Crime Much of the literature on precaut ionary behaviors has focused on the link between precautionary behaviors and personal fear of crime. There has been minimal research on precautionary behaviors and altruistic fear While individuals take part in precautionary behaviors to protect themselves, a more recent arg ument that has emerged is that many of the behaviors people participate are meant to provide and Ellison (2002) conducted one of the only studies to examine this facet of altruistic fear. Their study looked at thirteen different types of precautionary behaviors (including avoid going out alone, avoid going out at night, installed alarm, dead bolts, door chains, security fence, window locks buy firearm, buy dog for prote ctions, join community watch, carry weapon). Many of these were found to be reactions to altruistic fear rather

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34 than personal fear. When participants indicated being fearful for their spouse and/or daughter (s), the likelihood of engaging in a precautiona family increased (Warr & Ellison, 2000). Two behaviors were found to be significant reactions for personal fear but not for altruistic fear not going out alone and not going out at night (Warr & Ellison, 2000). Nonetheless, gr eater research is needed in understanding and determining which reactions are a result of personal fear of crime versus altruistic fear. The current study worked to better understand the relationships between altruistic fear and the precautionary behavior s offenders participate in to protect their family. Measuring Fear of Crime: Offense types and fear Fisher, 2009). Its argued that by looking at crime as being one dimensiona l (or fear in general), we would be unable to capture the different levels of fear that individuals have for certain crimes compared to others (by offense type) (Rountree, 1998). The lists of crimes that have been traditionally used to measure fear include items that capture fear of both property and violent crimes (e.g. burglary, assault, murder, car theft, robbery, vandalism, etc.); these have been expanded and modified by several researchers over time (Ferraro, 1995). Studies have shown that many have no ted being fearful of some crimes more than others. One study found that individuals tend to be more fearful of property related crimes, such as their homes being burglarized or their cars stolen or broken into (Rader et al, 2007). Fewer individuals have i ndicated being fearful of violent crimes like being murdered or raped (Rader et al, 2007). However, women, especially white females, have been found to be more fearful of violent crimes (usually crimes like sexual assault or rape) than minorities or men ( Rountree, 1998; Warr & Ellison, 2000).

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35 Yet this is not necessarily true in non white communities (Rountree, 1998). Rountree and Land (1996) found that indicators of vulnerability (i.e. burglary victimization) and fact that there is variation among the types of crimes that individuals can be fearful of, one would expect that offenders who are fearful of crime are also fearful of a variety of crimes. The present study hopes to better understand what crimes offenders are fearful of and the effects of offending on their fear levels.

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36 CHAPTER 3 RESEARCH METHODOLOGY The current study examines the following research questions and hypotheses: Personal F ear of Crime and Offending Research Question 1 Are more serious offenders less fearful of crime? If so, what types of crime? Hypothesis 1 The author only knows of one other study that has examine d this relationship among adult offenders (Lane & Fox, Forthcoming). As a result, the current hypothesis basically exploratory and is using the work of Lane & Fox (Forthcoming) as a guide in determining expected relationships. We expect to find a negative relationship between the seriousness of past criminal offenses committed and their fear of crime. Specifically, we expect to find that as the severity of crimes committed by the probationers increases the less fearful they will be overall and the less fear ful they will be of crimes that are less serious. We anticipate that offenders generally will not be afraid of crime; however, they may be more afraid of more serious crimes than non serious ones. These expectations are based the findings of Lane & Fox (Fo rthcoming), who found that inmates reported not being fearful of crime overall. Personal Fear of Crime and Social Disorganization Research Question 2 How do perceived neighborhood characteristics (e.g. disorder, cohesion) affect for themselves and for their families?

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37 Hypothesis 2 We expect to find that probationers who perceive their neighborhoods as being disorganized will indicate being more fearful of crime than those who do not perceive their neighborhood as disorganized. Sp ecifically, perceived negative neighborhood characteristics will have a positive relationship to fear. If probationers see their neighborhoods as a dangerous place to live, they will be consequently be more fearful of crime (especially if they are offende rs associating with other offenders). When examining fear, perceptions of disorganization have been found to be predictive of fear (Covington & Taylor, 1991; Lane & Meeker, 2003; Maxfield, 1984; May et al., 2002). Studies that have examined fear and the ne ighborhood among offenders have indicated that increased perceptions of disorder also indicate higher fear levels (Lane & Fox, Forthcoming; May, et al., 2002). Personal F ear of Crime and Precautionary Behaviors Research Question 3 What precautionary beha viors do probationers take part in to cope with personal fear of crime? Are more serious offenders likely to use defensive behaviors (defensive vs. avoidance behaviors)? Hypothesis 3 We hypothesize that a prior offense history will lead individuals to fi nd methods to protect themselves. We expect that offenders who have more serious criminal history will engage in defensive behaviors, rather than avoidance behaviors, to cope with crime. We also expect to find that male probationers will be more likely to participate in defensive behaviors and female offenders will be more likely to indicate they participate in avoidance behaviors due to fear. This is consistent with the findings of May (2001)

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38 and Lane (2009), who looked at precautionary behaviors patterns among juvenile offenders. Altruistic Fear of Crime and Offending Research Question 4 Are probationers fearful for th eir family members ? How does this vary across gender? Hypothesis 4 To date there has been a limited amount of research on altruistic fea r of crime and there has yet to be a study that examines altruistic fear levels among offending populations. The seminal piece by Warr and Ellison (2000) examined altruistic fear extensively among non offending populations and (as noted earlier) found vari ations in fear depending on the gender of the participant and gender and age of the person for whom the respondent worried. Typically, women have higher levels of altruistic fear for younger female children than male children, and men typically have higher levels of altruistic fear for their wives than women do for their husbands. W e exp ect to find that offenders are more f earful for their families than for themselves based on the assumption that they have put their families at a greater risk of victimizati on in comparison to the probationers who have committed less serious offenses. When looking at gender, we expect to find that female offenders, compared to male offenders, will indicate greater fear for their children (especially higher fear levels for fem ale children), and men, compared to women, to indicate higher fear levels for their wives, and children than for themselves.

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39 Research Design Research Setting The setting for this study is Alachua County, Florida and access to probationers was granted thro ugh Alachua County Court Services Probation Division (located in Gainesville, FL) (Appendix A). Permission to conduct this study was obtained through The Institutional Review Board at the University of Florida approved the study (see Appendix B). Alachua County has over 1600 individuals currently under supervised misdemeanant county probation who report to Court Services, which is the supervising probation agency in the county. This provided researchers with a large population from which to sample for the present study. The local probation clients vary on personal characteristics such as gender, race, and socio economic status, providing a diverse group of community corr ections clients to study. Because probationers remain in the community while under correctional control, they were an excellent source of information about the effects of neighborhood factors on fear of crime among offending populations. Population and S ample Selection The population for this study was comprised on individuals who were on misdemeanant probation during the time of data collection. These were individuals who were on county level probation for committing one or multiple misdemeanor offense( s), including various property, drug, and violent crimes (some individuals could have been placed on county probation for low level felonies).

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40 Probation staff provided researchers with a list of probationers who were serving their sentence on May 25, 2010 The probationers on the list were at different points in their probation sentence, including those who began their sentence months before this date to those who began their sentence the day the list was compiled. On this day there were 1,651 individuals on probation. However, in order for probationers to participate in the study, they had to meet a set of criteria. Researchers 1 took the list of active probationers and used the following set of criteria to create a modified list of eligible participants to ensure that selected probationers would be able to participate during the anticipated timeline of the study. Probationers had to be over the age of 18, reside in Alachua County and report to Court Services office in Alachua County. Additionally, the proba tioners had have at least four months left on probation in order to be eligible to participate (this criterion being the most important to reduce the chance of individuals being released during the data collection process and to take into account those who qualify for early termination). After eliminating all those individuals who did not qualify from the original list (460 probationers removed due to ineligibility based on the above criteria), researchers were left with a population of 1,191 individuals fr om which to sample. Population and S ample S election (Random Sample) There were two sampling methods used in order to obtain the sample used for the study. Once those who met all the criteria were identified, a list was made of all possible participants f rom which to randomly sample. This list was sorted in a random order to ensure that the probationers were not listed in a specific way (e.g. by alphabetical order, 1 This project is being conducted jointly with Saskia Santos, Ph.D. student in Criminology, Law and

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41 numerical order, probationer ID, probation officer, probation status, offense type, etc.). O nce the potential participants were placed in an unsystematic order, they were randomly sampled by flipping a coin to determine which individuals would be asked to participate in the study. Those who got heads were not selected for the study. Those who got tails were selected to participate in the study. This was done until we reached 450 probationers. After randomly sampling from the list of eligible participants, researchers recognized that some individuals who were originally selected were in fact ineli gible, as system used by Court Services Probation staff to maintain electronic files for every probationer) 2 rrent on official status was unchanged. As a result, researchers went through every probationer selected and removed those who had been violated, sent back to jail, or place d on mail in status or compliance probation. This resulted in a significant loss of individuals who had been selected to participate in the study (243 probationers were removed after accounting for change in status). Because only 207 probationers were left from the originally sampled list, researchers resampled from the population in the original list of eligible participants. Due to the fact that there were individuals who were ineligible after going through probation officers notes, the same procedure wa s done to the remaining 741 cases that we could sample from. Of the 741, 272 were found to ineligible, again 2 The MONITOR system allows probation staff to post notes and updates on the probationer for every meeting they have with them. This includes progress on their sentence, any violations, reporting times, progress in programs, payment of fees, etc.

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42 either because of change in status for violation, return to jail, early termination, mail in status, etc. This left only 469 individuals from which to sample that were eligible to participate in the study. Researchers randomly sampled 243 individuals using the same procedure used to obtain the original random sample (listed individuals in a random order and then flipped a coin to determine selection in the study), leaving researchers with a final random sample of 450 probationers. This group was then assigned a three digit random subject identification number (ranged from 001 to 450). This allowed researchers to identify participants while reducing t he risk of having their identity revealed. Researchers had a master list with the name and subject number of each participant. The list was kept in an envelope, and separate at all times from all other project materials (was locked in a cabinet throughout the course of the project). Population/Sample Selection (Convenience Sample) The second sampling method used for this study was a convenience sample (this was due to low response rates of those randomly selected (Of the 450 randomly selected only 153 c hose to participate)). While researchers understand the importance of having a random sample, in order to have a large enough sample size, the study was opened to all probationers in the last few months of data collection in hopes that the sample could be significantly increased. Reasons for low response rate were beyond the control of the researchers, as many individuals that were selected to participate were unable because of early termination, or a change in their status of probation (e.g., violation of probation or VOP, return to jail, etc.), or lack of interest. We were unable to go back to the originally generated list and randomly select more individuals for the following reasons: probation staff and officers only anticipated having researchers in

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43 the ir facility until the end of September of 2010, and many of the probationers on the original list had either had their probation end, changed to administrative status, or were violated and had their probation terminated. The convenience sample was assigned separate research subject numbers (starting at 500 so that the convenience sample could be clearly separated and identified from the random sample). Allowing more probationers to participate aided us in getting closer to our desired a sample size of 250 (based on power analysis). Response Rate Although researchers made several efforts to contact eligible participants for participation in the study, response rates among those eligible was much lower than anticipated. Of the 450 eligible individuals random ly sampled, only 153 (or 34% of the randomly sampled 450) probationers chose to participate in the study. Researchers made several efforts, as noted above, to recruit participants. Efforts included notification of the study by mail, by probation officer, and in person. There were several incentives for probationers to participate, yet recruitment and participation still remained low. After including those who were part of the convenience sample, the total number of probationers interviewed for the present study was 202. Due to variations in the number of individuals who chose to participate, response rates were calculated. Response rate is defined as the number of interviews completed, divided by the number of eligible participants in the sample (Skalland, 2011), The full sample of probationers included those who were randomly sampled and those who were part of the convenience sample (N=517). When looking at the response rate of the full sample, of the 517 probationers, 202 completed an interview (or a resp onse rate of 39%). Yet, there are multiple ways to look at response rate, because people failed to

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44 complete an interview for different reasons (Table 3 1). For example, there was a group of individuals who were eligible to participate but chose not to (tho se who refused to participate in the study due to lack of interest or because they had finished their community service and cost of supervision (n=65)). There were also some who failed to show up to the interview (n=79) or cancelled their interview appoint ments (n=10). Some became ineligible to participate (n=114) throughout the course of the study because of a change in their probation status. There was also a group of individuals with whom researchers never had any contact with or only had initial contac t. This includes participants who we had no direct (face to face) contact with (n=32), those who failed to report to the probation office (n=7), and those probationers with whom we had initial contact with and who said they would contact us to make an appo intment, but never actually made an appointment to be interviewed (n=8). The overall response rate for those who participated compared to those sampled (including all that we made at least one attempt to contact those who were eligible and those who lat er became ineligible but were eligible when contacted) was found to 39.07% (202 divided by 517). The completion rate was 100%, every person who showed up to the interview time completed the entire survey. This holds consistent with the other researchers wh o note that typical completion rates for interview surveys should be between 80% and 90% (Goyder, 1985; Orenstein & Phillips, 1978; Weisberg & Browen, 1977). The reason for 100% completion could be due to the interview nature of the survey or because of th e benefits that participants received 3 as a result of taking the survey (they could have felt 3 Participants were given either one month cost of supervision (equivalent to $50) or 5 hours of community services for participating in the study.

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45 like they should help us because we are helping them) (participant benefits will be addressed in a later section). Specifically, the cooperation rate was also ca lculated (as response rates are based on these two factors) (Langer, 2003). The cooperation rate looks at the number of interviews completed divided by all participations that were eligible to participate (including those who chose to participate and those who chose not to participate but met the eligibility requirements of the study) (Langer, 2003). As noted earlier, a significant number of probationers became ineligible to participate in the study (n=114), most who became ineligible did so because there s tatus changed to VOP (violation of probation), their probation ended early (n=17), or their status changed to mail in, so they were no longer reporting to the probation office (n=20). The cooperation rate was 50.1%. Recruiting Participants: Procedure The participants who were randomly sampled were notified of the study using four approaches. First, selected participants were sent a letter through the mail that described the study to them (Appendix C). The letter included information regarding what the s tudy was about, potential benefits to participating, and who to contact if they were interested in being a part of the study. Specifically, the letter indicated that participation in the study was voluntary and that the researchers were available during re porting days at the Court Services building or by phone to answer any questions they may have concerning the study or participation. The letter also indicated the possibility of getting the five community service hours or cost of supervision credit if ther e were no community service hours assigned in their case. Additionally, the letter indicated that the researchers would have a list of scheduled times that they could sign up for to meet

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46 with the researcher to be interviewed one on one. Essentially, resear chers had a list of times, each about an hour and a half long, that they made available to interview the participant one on one. Probationers were notified of the available times and days from which to choose. If those times were not convenient for the po ssible participant, researchers scheduled alternative times and locations with the participants for an mail and phone number to allow the probationers to contact researchers to schedule an interview. The phone number was from a phone purchased solely for use in this research project. Researchers carried this phone with them at all times to schedule interview times with participants and contact participants to confirm interview times or reach them if they failed to show up when scheduled 4 The second way in which researchers tried to recruit participants was through the probation officers. After briefing probation officers about the project, the officers agreed to aid research ers with recruiting participants. The probationers that were randomly selected were organized based on probation officer caseload. Researchers put letters officer. Probati on officers agreed to hand probationers letters describing the research project when they met with them for their monthly visit (these letters were the same as those that were mailed to them) (Appendix C). This allowed us to reach those possible participan ts who did not check their mail or had an old, incorrect, or invalid mailing address. The probation officers were made aware of the study and the possible benefits 4 Researchers purchased a disp osable phone with a separate number for possible participants to use if they have questions or want to set up an interview time. This facilitates the scheduling of probationers, knowing that there is a separate line specifically for probationers to call an d ensures the safety of researchers by not having to give out personal phone numbers.

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47 it presented to the probationers, so they could answer questions or relay our information to the probationers in the most effective and comprehensive way. Most probation officers were able to give all letters to the designated potential participant. Many gave us back the letters for those they were not in contact with each month, so that we coul d find alternative means of contacting that individual (or wait until the next month for reports these were often those who were eventually given a VOP or were switched to an administrative status). The third way researchers tried to recruit participant s was by being present for several months at the building where probationers were required physically to report probationer who did not receive a letter in the mail o r for some reason was not advised by his/her probation officer of the study to have an extra opportunity to learn about the opportunity 5 Researchers were provided with the days and times that the sampled probationers were scheduled to report by probation staff. Some probation officers gave us a list of those we selected with the times and days they were scheduled to report to facilitate recruitment at the Court Services building 6 Researchers also had access to to look on the system to retrieve similar 5 After briefing staff on the project, most were willing and enthusiastic about the study. However, there were some who had hesitation in having probationers on their cas eload participate. Although there were only a few who felt this way, it did have an impact in our ability to recruit participants as effectively as we would have wanted. Researchers made several attempts to speak with each probation officer and answer any questions or concerns they had about the study. 6 Recruiting participants was often dependent on the probation officer, many staff members worked with us when in the court services building recruiting by coming over and asking us which probationers on the ir case load we were trying to get a hold of that day, updating us on the status of any probationer on our list, and directing probationers directly to us after their meeting with them.

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48 information as well 7 Researchers stood in the waiting room and approached only those probationers that were selected to participate. We made it clear to the probationers that we are not associated with Court Servi ces and that refusal to participate will not affect The fourth and final way that researchers tried to recruit participants was by passing out letters to all probationers who reported to Court Services (after the random sample failed to obtain the desired number of participants). This allowed researchers to sample probationers who were not originally selected to participate, to be included in the convenience sample. Due to the fact that the County Probation St aff only allowed us to recruit in person for a couple of months, those participants who we were unable to reach during those months were sent a follow up letter notifying them of the study one more time (third notification of the study). The letter includ information so that they could call to set up an appointment for a time, place, and day at their convenience (Appendix D). The letter also notified them of the potential benefits to participating in the study. Participant Benefits The Alachua County Court Services probation staff approved the researchers to give participants a benefit for taking part in the survey (Appendix E). Individuals who choose to participate were eligible to receive 5 hours of community service credit or one month worth of cost of supervision (COS) credit. Participants were made aware of the opportunity prior to beginning the survey. Court Services added the study to the list of 7 Although we were given the date and time probationers were schedule d to report, some probationers would fail to show or would show up at different times than what they were scheduled for, which made it more difficult to recruit selected participants.

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49 approved community service projects In both probationers who were part of the convenience sample and those probationers who were identified through the randomization process were eligible for credit. Those who chose to participate that were not assigned to complete community service were given the possibility of getting cost of sup ervision (COS) credit in the amount of one month of credit (which is the equivalent to $50). However, participants were only allowed to receive one type of credit and could not choose which type of credit they would receive. If they were required, as a p art of their conditions, to complete both community service and cost of supervision, they only received credit for community service 8 At they end of every week researchers emailed each probation officer with the list of probationers on their caseload that participated in the study. Probation officers then designated the appropriate credit for each participant. Individuals who did not qualify or chose not to participate in the study were not penalized; there were other approved opportunities available to pr obationers to complete community service hours. Setting up Interviews After agreeing to participate in the study, probationers were informed about the available scheduled meeting times to be interviewed. If these times did not work, researchers informed t he probationer that we could set up an alternative interview time and date that is most convenient for the probationer. Interviews were conducted in the Court Services building in a room away from the probation staff offices and in a room that has doors wh ich close (e.g., conference room in a waiting area and on the second 8 There were some occasions where probation officers allowed probatione rs to participate in the survey and get credit for other conditions of their probation. There were many who received credit for work crew days after participating in the study. This was not suggested in any way by the researchers and was solely based on th e decision and discretion of the probation officer.

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50 floor away from probation staff). The interviews were not conducted in the presence of Court Services staff or anyone who was not associated with the research project. Because many probat ioners could not be interviewed during the hours or days that Court Services was open, researchers accommodated and worked around the Services building, other possibl e meeting locations were coordinated, including different branches of the Alachua County library and other public locations in the community that were conducive to conducting interviews (coffee shops, book stores, etc.). When a probationer failed to come t o their scheduled interview, the researchers made attempts to contact that person to reschedule the interview for a different date and time. Researchers only made three attempts to contact probationers. If the participant indicated that he or she was no longer willing to participate in the study, he/she was taken off the list and was not contacted again. If a probationer said they were not interested in participating at any point, we crossed them off our list and did not make any other attempts to recruit them. Researchers kept a behavior log, which recorded information like: failing to show up to an interview or those who indicated they did not want to participate for reasons such as, not being interested in the study, having to travel from other cities, transportation issues, or already having completed their community service or paid off their cost of supervision. The behavior log also documented information about participants arriving late, rescheduling, or leaving the study early (although none failed to complete the interview).

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51 Official Records Data Procedure file so that we could obtain their background information. This allowed the researchers self report responses to their official criminal history and compare across probationers. The information in the criminal history files includes: criminal history (local, state, and out of state records) and demographic information. Although much of the i nformation that was obtained is public record, due to the sensitivity of some of the information, all researchers were certified through Florida Department of Law Enforcement (FDLE) prior to obtaining access to records and were legally bound to confidentia lity. To obtain the official criminal histories, researchers gave a list of all the probationers name, race, and gender to Court Services. Records staff took our list and produced the paper copy for each official criminal histories from the FCIC/NCIC data base. Official criminal records generally were handed to researchers every week or every couple of weeks. Researchers used criminal records, along with MONITOR, the Court Services probation database, and information from LINDAS 9 (Legal Information Network Data Access System), the court records database, to complete the information on the criminal history forms 10 The researchers had a criminal history form that was used to record and collect ory form has been 9 LINDAS and MONITOR were used as supplements to the official criminal record to help add, clarify, or fill in any missing information that was not found or missing from the criminal record pulled. Infor mation like conditions of probation, fees due, and length of current sentence were found by accessing these databases. Court Services staff gave us prior clearance and supported us in using these databases for the current project. 10 Criminal History forms were completed and entered by Saskia Santos, PhD (the other principal researcher on this project).

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52 name on a cover sheet. The cover sheet had instructions to remove the sheet and then place it in an envelope once the criminal history form was completed. The subject number was placed on the first page of the actual criminal history report, leaving the subject number, not a name, as the only identifier that corresponds with the survey instrument. This was necessary to match the criminal history fo rm to the survey instrument later by subject number. This helped protect the participants by ensuring that that their responses could not be linked back to them. The criminal history form itself included demographic information, criminal history informatio n, where each arrest charge (including level and degree) occurred, the state where it occurred, the year it happened, and the outcome of that arrest (which varied from probation to jail time). The sentence length was also recorded on the form. Other inform ation included current probation sentence, probation sentence length, and official probation conditions. Having probationers conducted the interviews (i.e. it did not effect t he researchers behavior, demeanor, or manner in which they carried out the interview with the probationer. 11 ) All criminal history forms were kept in a locked file cabinet at the University of Florida. After completing the criminal history forms, all offici al criminal records were destroyed and disposed at a Court Services building location, where they have designated bins for such material. 11 On only one occasion did one of the researchers have to change the location of the interview after obationer had been charged with a sexual offense (2 counts of lewd and lascivious conduct) the nature of this offense meant that the offender could not be within a certain distance of minors. As such, we moved the interview to another location that was mor e appropriate. However, the researcher did not treat this participant differently or conduct the interview differently.

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53 Semi Structured Interviews Procedure When the probationer arrived for the interview, they were first given an informe d consent. The informed consent was read aloud to the participant as they followed along (this was done for all participants). The informed consent described the study, the purpose of the study, the rights of the participant, and the potential risks and be nefits associated with the study (Appendix G). Participants were notified that their responses would be tape recorded throughout the course of the interview. The researcher asked every participant if they had any questions prior to beginning the interview. After reading the consent form aloud, if they agreed to participate, they were asked to sign and return the consent form to the researchers. Participants were given a copy of the informed consent to keep for their own records. Once a signed informed conse nt was obtained, the researcher then completed the first page of the survey and removed it from the survey instrument. The first page of the survey had administrative components, such as name, and the credit). This ensured that a possible participant was not interviewed more than once and helped keep records of who conducted each interview. Once the cove r sheet was removed, both the cover sheet and the informed consent were placed in an envelope so the three digit subject number on it, which helped ensure that the only way to match a subject number to a participant name would be through the master list and not from the instruments. After placing the informed consent and first page of the survey in the envelope researchers began the interview. Due to the fact that the in terviews were conducted one on one, the entire survey was read aloud to the participant, and the

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54 helped guarantee that all probationers could understand and participate in t he study, regardless of literacy level. The questions on the survey were either open or close ended, depending on the information sought. For many of the close ended questions, researchers created a set of colored cards for each set of response options. This facilitated the interview process and made the response options clear to the participant for each set of questions. When a participant was asked a close ended question, the researcher handed the participant a specific colored card with the answer sele ctions for that particular question on it and researcher then recorded their responses on the survey instrument. The instrument also indicated to the interviewer which card to give the participant and when to collect the card from the participant (Appendix H). So the researcher only gave a card with answer options to the participant when it was related to a specific question and collected it when it was not relevant. Bec ause some individuals may have difficulty reading or understanding the choices provided, the researcher read and explained each of the answer options following each question. The researcher then read the questions to the individual and circled the particip ants chosen response. Open ended questions were tape recorded to allow for precise transcription of the ended, the tape recorder was turned on, and once the participant completed th eir response, the researchers turned the tape recorder off. The survey instrument designated to the interviewer when to turn the tape recorder on and off. The interviewer was asked to

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55 notify the participant every time the tape recorder was turned on or off Throughout the interview, the researcher reiterated to the participant that they were not to use their name/nickname, names of family or friends, or describe details and events that could identify the person or others while the tape recorder was on. This was continually reinforced to protect the identity of the participant. The researcher also informed the person that if he or she happened to reveal any information that could identify him or her during the interview, the researcher would delete the inform ation while transcribing the tapes. The tapes from the interviews were transcribed verbatim except any names or personal identifiers, which were removed 12 The tapes and transcriptions were coded arate from the matching list, signed informed consents and surveys. Once the interviews were transcribed the tape recordings were destroyed. All tapes were transcribed within 40 days of the interview (as requested by IRB). However, there were some occasion s where participants responses could not be recorded on tape, reasons include the following: participants asked that their responses not be tape recorded, the participant was difficult to understand (this was often due to health issues that did not allow t hem to speak loudly or clearly), the participant did not speak English, and/or there was not enough privacy in the location where the interview was being conducted 13 Whenever this 12 University undergraduate research assistants transcribed recordings over the course of three semesters. Research Assistants were taugh t how to transcribe interviews and signed a confidentiality agreement before beginning any transcriptions. One group of research assistants transcribed the interviews and another group of research assistants checked the transcriptions and checked for any e rrors, inaudible words or phrases, or missed words or phrases. Transcriptions were re checked by researchers to ensure that interviews were being accurately transcribed. 13 Most interviews were conducted in the public library in Alachua County, where priv ate rooms were checked out for the interviews. On some occasions, either rooms would be full or a probationer signed up

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56 happened, researchers hand wrote their open ended responses in the space pro vided to the best of their ability. Researchers made every effort to write down verbatim what the participant said. In cases where there was limited privacy (i.e. the general floor of the library, a Starbucks, a Subway, another restaurant), some participan ts felt more comfortable writing down their responses to ensure that their information was kept private. Researchers wanted participants to feel comfortable and worked with participants when necessary. To ensure that accurate and appropriate information wa s given, researchers read the information to ensure that it was legible and answered the question asked. The interviews generally ranged from 45 minutes to 1 hour, depending that lasted over 3 hours. When the interview was completed, the participant was thanked for their participation and notified that their probation officer would be informed by the end of the week of their participation in the study. Each probation officer was given a weekly list of those probationers on his/her caseload that participated in our study so that the participant could receive the every month with a full list again that included all probationers on their caseload that participated that month. This reminder helped ensure that probation officers gave participants the promised credit. They had two separate lists to reference. There were only a few cases where pro bationers where not given credit immediately; however, this to participate last minute so there was not enough time to reserve a private room, interviews were conducted on a table in the library o r in a Starbucks. In such cases, there was often a lot of noise around us (so the interview would not have been able to be heard on the recorder) or the participant did not feel comfortable responding to certain questions loud enough for the recorder. As a result, researchers took down detailed notes to make the participant feel comfortable and ensure that the qualitative data was obtained.

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57 was quickly corrected by emailing and calling the probation officer personally so that the probationer would not face any consequences (i.e. being violated). In all cases where this occurred, part icipants were immediately given credit and their probation status was never negatively affected as a result of participation. At the end of data collection, researchers emailed a complete list of all probationers that participated in the study from the beg inning to the end of the project. Probation officers were asked to send us back a confirmation email to ensure all participants received credit. Interview Variables to be used in this Study The survey (Appendix H) contained several questions including q uestions on fear of crime, altruistic fear, precautionary behaviors, neighborhood perceptions, and some questions designed to obtain demographic information. The questions in the survey were taken from or adapted from the previous work of other researchers who have studied fear or crime and social disorganization (Appendix H). Open ended questions were asked as well, which allowed participants to answer questions with detailed (qualitative) responses. The following section will describe each of the variabl es used in more detail. Operationalization/ Measures There are several independent and dependent variables and some are measured in both qualitative and quantitative ways. This section will list each of the variables used and how they were operationalize d, first addressing the quantitative dependent and independent variables and then the qualitative variables being measured. Dependent Variables The following quantitative variables were used as dependent variables in the present study.

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58 Fear of crime Fe ar of crime was measured by asking participants the following question : I would like to ask you about how personally afraid you are of the following crimes. For each of the following crimes please indicate if you were not afraid, somewhat afraid, afraid, or very afraid. In the past year how personally afraid have you been of: (Appendix H for instrument) Participants were asked how afraid they were about 21 different crimes including being robbed, raped/sexually assaulted, being murdered, being attacked wi th a weapon, being physically assaulted, being shot at, being the victim of a drive by, being harassed, being carjacked, having their car stolen, having their property damaged, having their property damaged by graffiti tagging and having their money or pro perty taken from them without force and with force, being approached by a beggar, having their home burglarized while they are present and while they are away, and being around drug use or sales. The use of these crimes is consistent with previous research on fear and range from minor offenses to more serious offenses as used by LaGrange and Ferraro,1989, Lane, (2006,2009) and Warr, 1984. Using a Likert scale, response options ranged from not afraid (coded as 1), somewhat afraid (coded as 2), afraid (coded as 3), and very afraid (coded as 4) (see Lane & Meeker, 2003). conducted in order to determine the best approach to combine the items used to measure fear. First, b ivariate c orrelations were examined. All of the items were significantly and positively correlated with one another. In fact there were a few items that had particularly high correlation coefficients (Being attacked with a weapon had a correlation coefficient of .8 12 and having your money taken with force had a correlation coefficient of .818 both of these were significant at the .01 level). However, these

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59 items were combined into two separate indexes. Correlations were also run for the indexes, which showed to be significant but no issues of multicoliniarity were found. Second, prior to creating indexes, I conducted Principal Components factor analysis using Varimax rotation with Kaiser Normalization to determine the most appropriate way to create the indexes. Aft er conducting factor analysis, almost all of the items loaded on to two separate components (Table 3 2). The way that the items loaded on to the two factors was consistent with previous research and with what was theoretically anticipated with personal/vi olent crimes loading on the first factor and property related crimes loading on the second factor (Table 3 2) (Ferraro, 1995). Two items that were items, which are both types of harassing behaviors (considered as personal crimes), loaded on to the second factor (where property crimes loaded, possibly because beggars often ask for money). Because these two behaviors are not considered property crimes, they were omitted and removed and factor analysis was run again, where the rest of the items loaded as anticipated. Based on factor analysis results, three indices were created by summing the responses for individual items (which range from 1 ( not afraid ) to 4 ( very afraid )) for each index and then dividing by the number of items used in each index to create a score consistent with the original coding scheme. The first index created was a general fear of crime index, where all 21 items in the instrument w ere combined. The second index created was a violent/personal crimes index. This included 13 items (murder, being attacked with a weapon, being robbed, threatened, beaten up, shot at, drive by shooting, physical assault, sexual assault, being harassed, car jacking, and having

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60 property taken with force). A property crime index was created that included 6 items (break in, car theft, property damage, property damage by graffiti, break in while away, having money or property taken without force). All three ind exes were found to have drug drug crime independently. Altruistic f ear Altruistic fe ar was measured two ways. The first variable provides a comprehensive measure that is inclusive of all individuals, family members and non family members with whom the participants may have lived. The second measure allows focuses on individual family memb ers. First, participants fear for other members of their family/household was measured by asking participants the following question: qually afraid for other people living in your Parti cipants were given a 3 point Likert scale, where response options included more afraid (1), less afraid (2), and equally afraid (3). These were recoded so that 3 = more afraid and 1 = less afraid (See Appendix H) Altruistic fear was also measured by askin g participants: Now I would like you to think of your family members. Of those living in your home, please indicate how personally afraid you are that each of the following family members will be a victim of crime? Participants were asked about how afrai d they are that their father, mother, husband, wife, partner, son(s), daughter(s), brother(s), sister(s), or other person will be a victim of crime. Response options were not afraid (1), somewhat afraid (2), afraid (3),

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61 and very afraid (4). For those who d id not live with any family members or did not have Because many individuals may live with roommates other than family members an measures were adapted and modified based on questions used in Warr and Ellison (2000). Altruistic fear has been studied by looking at of descriptive sub analysis will be conducted with this variable so that altruistic fear can be examined by the gender of the participant and the gender of the family member. Due to the small sample size (n=202) and the limited number of probationers who indicated living with each type o f family member, only descriptive analysis was conducted. There were several variables constructed to examine altruistic fear using these items. First, three scales will be made that distinguishes between spouse, children, and parents. Second, each family member that was asked about (i.e. mother, father, wife, husband, son, and daughter) will remain as separate variables (again so that variations across gender and groups of family members can be conducted). Due to the fact that many participants indicated either not living with family members (coded as 97) and those who did live with family members most often indicated not being afraid for them the distribution is highly skewed. As such, the response options for these variables will be collapsed and dichoto mized. Those who indicated being not afraid (1) will be recoded as Not Afraid (0) and those indicated being somewhat afraid (2), afraid (3), or very afraid (3) were collapsed and dichotomized and recoded as Afraid (1). Those who were coded as a 97 were rem oved from analysis, and the descriptive analysis only included those who indicated living with each type of family member.

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62 Precautionary b ehaviors Precautionary behaviors were measured by asking participants the following question: Now I would like to a sk you about some of the things that you have done to protect yourself from crime. Please remember your answers are confidential and if you prefer not to answer a question you may skip it. In order to feel safer from being a victim of c rime, in the past ye ar did you. Participants were asked if they took 12 different precautionary behaviors based on studies by Ferraro (1995), Lane (2009), Lane and Meeker (2004). The 12 behaviors included buy or secure a gun, carry a gun, carry a weapon other than a gun, ar range to go out with someone so they would not be alone, avoid certain areas of their neighborhood or community, join a gang for protection, hangout with gang member, buy an alarm or security system, install extra locks on their home or car, buy a watch do g, added outside lighting, and/or limit or change their daily routine because of crime. The response options were yes (coded as 1) and no (coded as 0). Bivariate correlations were first conducted and all items were highly correlated with one another, howev er, issues of multicoliniarity are not an issue because indexes were created. Principal Components Factor Analysis with Varimax rotation was conducted to help determine the most appropriate way to create indexes of these behaviors. Factor analysis (Table 3 3) revealed three separate components. Defensive behaviors loaded on to the first factor, avoidance behaviors loaded onto the second factor and target hardening behaviors loaded onto the third factor. This is consistent with prior research and was antici pated. Three indexes, as shown in Table 3 3, were created for this variable where 3 items (buy of secure a gun, carry a gun, carry a weapon other than a gun) were placed into one index that representing defensive behaviors. The second index is for

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63 those be haviors that are known as target hardening, which includes 4 items (buy an alarm or security system, install extra locks, add outside lighting, and buy a watch dog for protection). The final index includes avoidance behaviors, which is comprised of 3 items (arrange to go out with someone so you are not alone, avoid certain areas of your neighborhood or community, limit or change your daily routine). This variable will serve as the dependent variable for research question three. Independent Variables The f ollowing section describe s each of the quantitative independent variables in the present study ( see Appendix H for questions in survey instrument ). Offense hi story Offense history was measured in two ways: official and self report data but only official records are used in the present study because they were more complete source As a result, self report data were not used in the present studies analysis to indicate criminal history. previous and current offense history as it appears on the criminal record in the Florida and National Criminal Database (FCIC/NCIC). The information obtained from the criminal history forms (See Appendix F) allow s us to look at the offense history for eac h participant so that it can be examined in comparison to their fear responses. Variables from the criminal history form were used as predictor variables in three research questions of the present study. Offense history is used as an independent variable to examine: 1) How themselves? 2) Are probationers who commit more serious offenses more fearful of crime for themselves or their family members in comparison to les s serious offenders?

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64 3) Are more serious offenders more likely to use defensive behaviors versus avoidance behaviors? Offense history variables were obtained by listing offenses verbatim in the order that it appeared in the criminal record and the degre e of offense, which was listed by indicating if each offense was a misdemeanor or felony and if it was a first, second, or third degree level offense as indicated in the criminal record. Each offense had listed the state and/or county the offense was commi tted in, case number, and date of arrest. We indicated the length of their sentence -for those who received probation or prison time their time was recorded in months; for those who receive jail time, we indicated time in days. We also used current offense history variables. The criminal history form lists several common offenses for those on misdemeanant probation, as well as having another column for those whose current offense is not listed. For e very offense they currently were charged with, researchers listed the case number for each charge to ensure accurate data information. Howe ver, it is important to note that these forms only had the participant s subject number so that there was no identifying information on them (no one could see it and know whic h participant s history record form it was only the two principal investigators had a maters list in a locked cabinet) (Appendix F). Official criminal record was measured three different ways here. First, there is a frequency measure across all crimes. This indicates the number of offenses an individual has participated in. Second, four separate variables were created for each type of crime (violent/property/drug/public ordinance). These were each dummy coded, where 1 = present and 0 = not present. Thir d, the final measure created was a seriousness scale. Within each type of crime (drug, property, persons/violent, public

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65 ordinance), offenses were separated into categories first by level (Misdemeanor or Felony) and then by the degree (first, second, or t hird degre e M/F). This is how the data were originally coded into the criminal history form and was separated into type of offense based the categories used by Alachua County Court Services (Appendix I). Each type, level, and degree was entered as c ount da ta. Researchers used these data to create an ordinal scale through a series of recodes. First, all offenses were combined into a new variable by degree and level. So those that were categorized as a Criminal Felony in the First Degree were added together t o create a Criminal Felony Frist Degree Variable (i.e. CF1 Drug + CF1 Property + CF1 Violent/Persons + CF1 Public Ordinance). This same process was conducted for those offenses that were classified as Criminal Felony in the Second Degree, Criminal Felony i n the Third Degree, Misdemeanor in the First Degree, and Misdemeanor in the Second Degree. So there are five variables, each measuring a different degree and level of offense (there is no longer a crime type distinction). Each of these variables were then dichotomized, so that a 0 indicates they did not have an CF1 or CF2 and so on and a 1 indicates having a CF1, or a CF2, or a CF3, or a M1, or a M2 (system missing were recoded as 0 as these were individuals who do not have a criminal history present). Th e next step was to recode the total for CF1 into a new variable where 1 was equal to 5 and all other was set equal to 0. CF2 was recoded into a new variable where 1 was equal to 4 and all other was recoded as 0. CF3 was recoded into a new variable where 1 is set equal to 3 and all other 0. M1 was recoded into a new variable where 1 is equal to 2 and all other were set equal to 0 and M2 was recoded into a new variable where 1 was equal to 1 and all others were recoded as 0. These new variables were

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66 then comb ined (NewCF1 + NewCF2 + NewCF3 + NewM1 + NewM2) to create a seriousness scale, where higher numbers on the scale indicates being a more serious offender. Social d isorganization Social disorganization was measured by several different variables. Such vari ables include perceptions of social and physical characteristics, to gain an accurate account of how participants view the communities they live in These measures used here are consistent with the measures used in the literature (Earls et al., 1994; Ferra ro, 1995; Lane et al., 1997; Sampson & Raudenbush, 2001). Gaining a detailed picture of the perceptions of the community that one lives in has been found to be a good predictor of fear of crime (Lane, 2002; Maxfield, 1984; Skogan & Maxfield, 1981). Social disorganization was measured through perceptions of four main social disorganization constructs: social disorder, physical disorder, collective efficacy, and subcultural diversity (i.e., ethnic heterogeneity). We also look at residential mobility as a characteristic that could affect social disorganization. Although some have argued that actual disorder (or objective measures of disorder) is important, perceived disorder has been f ound to be a stronger predictor for fear of crime (Covington & Taylor, 1991; Lane & Meeker, 2003). Furthermore, studies have shown that once other variables are controlled for, actual disorder, as a predictor, is greatly weakened (Lane & Meeker, 2003). Ph ysical and social disorder was measured by asking participants: I would like you to think of your neighborhood and some of the problems in your community and how serious they are. Please indicate if the following

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67 items are a big problem, somewhat of a prob lem, a problem, or not a problem ( Appendix H). Physical disorder was measured by asking participants how much of a problem the following were in their current neighborhoods: litter, broken glass, graffiti, buildings falling apart, trash on sidewalks, and needles on the street. Response options were on a four point Likert scale including: not a problem (coded as 1), somewhat of a problem (coded as 2), a problem (coded as 3), and a big problem (coded as 4). Social disorder was measured by asking participant s how much of a problem the following were: unattended kids, people selling drugs, people drunk or drinking in public, groups of teens or adults hanging out or causing trouble, poverty or financial hardship, gangs, gunfire, and people using drugs. Here the same response options were used, ranging from not a problem (1) to a big problem (4). All of the items used to measure physical and social disorder have been used in prior research of community disorder (Ferraro, 1995; Lane, 2009; Lane & Meeker, 2004, 200 5). F actor analysis was conducted, and all physical disorder items loaded onto one component (Table 3 4) and all social disorder items loaded on to one component (Table 3 4). As a result indexes for physical and social disorder were created by adding the items related to social disorder or physical disorder and then dividing by the number of items in the index. Reliability tests were pha of .945 indicating that both scales are highly reliable. Collective efficacy was measured by asking participants the following questions: something if they saw unatten

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68 analysis was conducted in order to determine how the items loaded. Factor analysis showed all items loading onto the same was also high at .815 (Table 3 5). These measures are consistent with previous work of Sampson et al. (1997) that combines elements of social cohesion and informal social control. Residential mobility was do individuals move in (3). illustrates how racially mixe following answer options the participant reports: not very mixed (1), most people are of the same race, somewhat mixed some people of different races (2), and very mixed, people are of various racial back grounds (3). As noted above scales were created for each of the variables (social disorder, physical disorder, and collective efficacy,) that are being used to measure social disorganization. Scales were created first by combining (i.e. adding) the items for each scale and then dividing by the total number of items being summed. Demographic Variables Demographic variables were used as control variables in most of the analysis and include: age, race, ethnicity, and sex. Age was determined by each partic was subtracted from the date of the interview to determine age. Race was measured by include:

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69 White (coded as 1), black/African American (coded as 2), and other (which will be coded as 3). A dummy variable was created for the race variable (i.e. white = 1 and non White = 0). Finally, sex initially was coded as female (1) and male (2). This was recoded so that females are coded as 0 and males are coded as 1. Ethnicity was options included His panic (1) and Non Hispanic (0). Qualitative Variables The instrument used in this study incorporated several questions to get qualitative information to allow for more detailed explanations from respondents. The open ended questions focused on and assessed four major areas: 1) Fear of crime, 2) precautionary behaviors, 3) a ltruistic fear, and 4) neighborhood perceptions. Within each of the four major areas, several themes were found in the transcriptions that were used for content analysis (Appendix I). All open ended questions in the interviews were transcribed verbatim, ex cept any names or personal identifiers, which were removed. A conceptual content analysis was conducted of the transcriptions in an effort to find major or meaningful patterns among participants. Researchers also conducted a qualitative comparison of parti presence of these themes 14 14 In order to conduct content analysis researchers utilized directed techniques (where analytic codes were created a nd based on theory and findings from past research (Berg, 2009). We also used a summative approach, where certain themes and ideas were found to be consistent throughout the interviews and were counted later added as themes (Berg, 2009). Moreover, all of t he interview data that was collected was transcribed from audio recordings and/or writings that the probationers indicated on the survey. From these interviews, researchers identified a series of themes that were consistently found and that were anticipate d based on past research and theory (so themes are not just an arbitrary set of categories) We focused the analysis on manifest content rather than including a interpretations of latent content for this study to reduce the error in interpreting probationer s statements and ensure that the content analysis was being conducted in a systemic and objective manner (Berg, 2009). Codes for these themes were then put into the four main categories: 1) fear of crime, 2) altruistic fear of crime, 3) precautionary behav iors, and 4) neighborhood perceptions. This allowed us to evaluate materials and find

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70 Fear of c rime Below are the open ended questions asked during the interviews concerning fear Do you feel that taking part in these activities [crime] has made you feel more or less afraid at happened to you? being examined. Altruistic fear of c rime The next set of open afraid for them [family] than your self? themselves in comparison to fear for their family and will also allow us to better understand how probationers own participation in crime has affected their fear levels. Precautionary b ehaviors The following questions pertain to precautionary behaviors and fear of crime. Participants will be ask meaningful patterns with regard to each of the 4 major categories. The qualitative data is later compared to quantitative findings found in the present study and were com pared to past research.

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71 that probationers have a history of engaging in criminal behavior, asking these questions will provide greater insight on how probationers choose to protect themselves from crime. Ne ighborhood p erceptions Finally, the following questions relate to fear and social disorganizati on. neighbo neighborhoods and community characteristics that could have an influential role in shapin g their fear. Analytic Plan I used a range of statistical analysis techniques to examine the relationship precautionary behaviors. This study used both quantitative and qualitative approaches to analyze the data collected from survey responses obtained from semi structured interviews. Table 3 6 outlines the analytic plan for each research question being studied here in detail. Quantitative analysis included descript ive statistics and frequencies, factor analysis, and reliability tests. Several regression models were estimated to examine relationships between the independent variables (which include social disorganization measures and official and self reported crimi nal history) and the dependent variables (which include fear of crime and precautionary behaviors)

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72 The first set of models used Step wise Ordinary Least Squares (OLS) multiple regression to predict fear levels among offenders. This allowed the researcher t o explore multiple independent variables of interest. As displayed in Table 3 6, the model explored how previous participation in crime, the type of offenses committed by probationers (persons/violent crime, property crimes, and drug related crimes), and n eighborhood perceptions (Table 3 8 shows measures) predicts the level of fear individuals have, after controlling for current offense and demographic variables. There were four dependent variables two indices (a general fear of crime index, persons/viole nt crimes and property crimes) and a drug related variable. The step wise regressions used a theoretical framework to add independent variable to the model at each step. Table 3 9 illustrates how variables were added to the model at each step. The second set of models, as shown in Table 3 6, used descriptive analysis to categories have an n that is less than 40), the most appropriate method on analyzing data on altruistic fea r is to look at descriptive statistics among this group. The third set of models, as shown in Table 3 behaviors. Previous offense history, offense seriousness, and current offense history, social disorganization measu use of precautionary behaviors. Three regression analyses were estimated, depending on how the dependent variable is examined. Logistic regression was used to examine s a predictor of precautionary behaviors, measured dichotomously as those who do partake in any of three types of precautionary behaviors (defensive, avoidance, and target hardening) and those who do not. Binary responses

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73 will be used to code precautionary behaviors for defensive, avoidance, and target hardening behaviors, so that 1 = a response of yes to one or all of the listed behaviors and 0 = no to all behaviors being examined. Table 3 10 shows how each set of variables will be added to each model. F inally, qualitative data was used to supplement quantitative findings. Content analysis was conducted on interview transcriptions that any significant patterns or themes can be noted among and across participant responses.

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74 Table 3 1 Full Sample Overview of All Participants (Non Interviewed/Interviewed Participants) Full Sample (N=517) % (n) Co nvenience Sample 13.2% 68 Original Sample 86.8% 449 Interviewed 39.1% 202 Refused to Participate (No Interest) 9.1% 47 Refused to participate (Done with CS/COS) 3.5% 18 No Show to Interview 15.3% 79 Canceled Interview Appointment 1.9% 10 No Longer Eligible Probation Ended 1.7% 9 Early Termination 3.3% 17 Administrative Probation 1.0% 5 Mail In Status 3.9% 20 Violation of Probation 12.2% 63 No Direct Contact 6.2% 32 Failed to report to probation 1.4% 7 Will Conta ct 1.5% 8

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75 Table 3 2 Fear of crime Factor Analysis: Factor 1 Loadings and Reliability Test N=202 Factor Loadings Alpha General Fear of Crime Index .960 Fear of Violent Crimes .958 Being murdered .877 Being attacked by someone with a weapon .849 Being robbed or mugged on the street .779 Being beaten up by someone .602 Being shot at while walking down the street .828 Being the victim of a drive by or random shooting .857 Being p hysically assaulted/attacked without a weapon .613 Being the victim of a car jacking .743 Having money or property taken with force or a weapon .829 Having someone commit a home invasion robbery against you .806 Having someone b reak into your home while you are there .629 Being Threatened by some .755 Being raped or sexually assaulted .827 Fear of Property Crimes .851 Having your car stolen .546 Having your property damaged .734 Having your propert y damaged by graffiti or tagging .650 Having someone break into your home while you are away .551 Having your money or property taken from you without force .610 Fear of Drug Crime (1 item Variable) Being around drug use or sale s Omitted Items: Beggar; Harassing 1 Principal Components Analysis Varimax with Kaiser Normalization

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76 Table 3 3 Precautionary Behavior Factor Analyses: Factor Loadings1 and Reliability Test N=202 Factor Loading s Alpha Avoida nce Behaviors .553 Limit or change your daily routine .646 Avoid certain areas of your neighborhood .610 Arrange to go out with someone so that you are not alone .685 Defensive Behaviors .622 Buy or secure a gun .793 Carr y a gun .830 Carry a weapon other than a gun .573 Target Hardening .688 Buy an alarm or security system .709 Install extra locks on your home or car .684 Buy a watchdog .645 Add outside lighting .658 1 Principal Compo nents Analysis Var imax with Kaiser Normalization

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77 Table 3 4 Physical and Social Disorder Factor Analysis: Factor Loadings and Reliability Test N=202 Factor Loading s Alpha Physical Disorder .832 Litter, broken glass, or trash on side walks or streets .701 Graffiti on buildings or walls .830 Vacant or deserted homes .842 Buildings that are falling apart or run down .824 Needles on the street .757 Social Disorder .945 Drinking .777 Selling Drugs .884 Tee ns hanging out .874 Poverty .783 Too many people in one home .748 Gunfire .711 People drunk on the street .821 Unsupervised youth .838 Kids behaving badly .868 People using drugs .841 Table 3 5 Collective Efficacy Facto r Analysis: Factor Loadings and Reliability Test N=202 Factor Loadings Alpha Collective Efficacy .815 Rely on neighbors for help .783 Help one another .803 Do something is kids are truant .687 Do something is see a crim e occur .647 Trust neighbors .774

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78 Table 3 6. Fear of Crime and Offending Research Questions Research Question Independent Variables of Interest Dependent Variables Analysis Plan How does offending and participation in crime affect probation crime for themselves? offense type (property, violent/persons, or drug crimes) or seriousness level predict fear levels? Key Variables: Criminal History Official Record: Offense (by type categories ( violent, property, drug) Offense Seriousness Scale Current Offense (violent, property, public ordinance, drug) Other Variables of Interest: Control Variables: Age, sex, race I would like to ask you about how personally afraid you are of the follow ing crimes. For each of the following crimes please indicate if you are not afraid, somewhat afraid, afraid, or very afraid. In the past year how personally Fear of Crime: Not Afraid (1) Somewhat Afraid (2) Afraid (3) Very Afraid (4) ***Note: The list of crimes that participants are asked to indicate how personally afraid they are of are the same as those that they are asked if they committed. Indices for fear of crime variable: Violent/persons crimes index 12 Items (rape/sexual assault, murder, being attacked with weapon, robbed, threatened, beaten up, shot at, drive by shooting, physical assault, harassed, car jacking, property taken with force) Property crime index 6 Items (break in, car theft, property damage, by graffiti, break in while away, having money or property taken without force. Drug related variable Ordinary Least Squares Multiple Regression Related Qualitative Variables of Interest : 1) Which crimes are you most afraid of? Why? 2) Which crimes are you least afraid of ? Why? 3) Please Describe which crimes you were a victim of and what happened to you?

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79 Table 3 6 Continued Research Question Key Variables of Interest eral are you more, less, or equally afraid for other people living in More Afraid (1) recoded (3) Less Afraid (2) recoded (2) Equally Afraid (3) recoded (1) ly afraid you are Not Afraid (1) Somewhat Afraid (2) Afraid (3) Analysis Plan Are probationers who commit more serious offenses more fearful of crime their family members? Descriptive Analysis Related Qualitative Variables of Interest: 1) Are you more afraid for them (family) than yourself? 2) Do you feel taking part in these activities [Crime] has made you feel more or less afraid of crime? Why? 3) Do you feel that taking part in these activities has made you feel more or less afraid for your family? Why?

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80 Table 3 7 Fear of Crime and Coping Mechanisms Research Question Independent Variables of Interes t Dependent Variables Analysis Plan How do probationers cope with fear of crime? Are more serious offenders more likely to use defensive behaviors? Key Variables: Criminal History Official Record: Offense Will be separated into offense type cate gories (violent, property, drug) Seriousness Scale An ordinal scale will be created to measure seriousness ranging from second degree misdemeanor to first degree felony. Current offense Other Variables of Interest: Control Variables: Age, sex, race, ethnicity. Now I would like to ask you about some of the things you have done to protect yourself from crime. In order to feel safer from being a victim of crime, in the Yes (1) No (0) ***Such precautionary behaviors will b e divided into precautionary v. defensive behaviors Precautionary behaviors: Avoidance behaviors: 3 items (arrange to go out with someone so you are not alone, avoid certain areas, limit or change daily routine,) Defensive behaviors: 9 items (buy or secure a gun, carry a gun, carry other weapon, join a gang, hang out with gang members, buy alarm or security system, install extra locks, add outside lighting, buy watchdog) Those who answer yes to engaging in any behavior will be coded as 1 and those wh o answer no to all will be coded as no Logistic Regression Related Qualitative Variables of Interest: 1) What crimes were you trying to avoid by taking part in the previously listed options? Please Explain. 2) Do you feel that doing these things h ave helped keep you safe? Please Explain How?

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81 Table 3 8. Fear of Crime and Social Disorganization Research Question Independent Variables of Interest Dependent Variables Analysis Plan 1) How do perceived neighborhood characteristics affect probatio ners fear levels for themselves and their families? Social Disorganization: Disorder: serious they are. Please indicate if the following items are a big problem, somewhat of a Not a Problem (1) Somewhat of a Problem (2) A Problem (3) A Big Problem (4) Physical Disorder: Litter, broken glass, graffiti, buildings falling apart, trash, needles on the street, vacant or deserted homes Social Di sorder: Unattended kids, selling drugs, drunk on street, drinking in public, kids misbehaving, hanging out & causing trouble, poverty, language and cultural difference, too many living in one home, gangs, people moving in and out a lot, using drugs, vanda lizing others property Collective Efficacy Residential Mobility Subcultural Diversity Other Variables of Interest: Control Variables: Age, sex, race, ethnicity, Previous offense history how personally afraid you are of the following crimes. For each of the following crimes please indicate if you are not afraid, somewhat afraid, afraid, or very afraid. In the past year how personally afraid have you been of: Fear of Crime: Not Afraid (1) Somewhat Afraid (2) Afraid (3) Very Afraid (4) Indices for fear of crime variable: Violent/persons crimes index 11 Items Property crime index 6 Items. Drug related variable (OLS) Multiple Regressions Rel ated Qualitative Variables of Interest: 1) How would you describe the people who live in your neighborhood in terms of income? 2) How would you describe the people who live in your neighborhood in terms of education? 3) What do you think you could r

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82 Table 3 9. Personal Fear of Crime Step Wise OLS Regression Overview: Predicting General, Violent, Property, and Drug Fear of Crime 1 Step 1 Step 2 Step 3 Step 4 Step 1: Controls Age, race, sex, ethnicity X X X X Step 2: Offense History CH violent, drug, property, public ordinance X X X Step3: Current Offense Violent, drug, property, public ordinance X X Step 4: Social Disorganization Social disorder, phys ical disorder, collective efficacy, residential mobility, subcultural diversity X 1 This series of analysis was done for all four type of fear that is being examined in the present study. Table 3.10 Precautionary Behaviors Step Wise OLS Regressi on Overview: Predicting target hardening defensive, and avoidance precautionary behaviors 2 Step 1 Step 2 Step 3 Step 4 Step 5 Step 1: Controls Age, race, sex, ethnicity X X X X X Step 2: Offense History CH violent, drug, property, public ordinance X X X X Step3: Current Offense Violent, drug, property, public ordinance X X X Step 4: Social Disorganization Social & physical disorder, collective efficacy, residential mobility, subcultural diversity X X Step 5: Personal Fear General, violent, property, drug X 2 This series of analysis was done for all three types of precautionary behaviors being examined in the present study.

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83 CHAPTER 4 RESULTS Descriptive Statistics Independent Variables: Participant c haracteristics The final sampl e for the present study was comprised of 202 Alachua County mis demeanant probationers. Table 4 1 displays sample characteristics for the full sample, as described here, and the breakdown among those in the convenience sample and random sample. Most of the participants in the study were men (n=128, 63.4%), with only 74 women in the sample (36.6%). Variations in racial and ethnic makeup varied, with most, 59.9% (n=121), identifying as white, 39.6% (n=80) as black, and 0.5% (n=1) as Asian. Only 6.4% (n=13) in dicated being Hispanic, 93.1% were of non Hispanic origin. There was a diverse age distribution ranging from 19 to 69, with the average age being 36 years old ((most individuals (59.8%, n=120) were younger in age nal background varied. Education ranged from 4 th 5 th grade (0.5%, n=1), 6 th 8 th grade (2.0%, n=4), 9 th 11 th grade (9.4%, n=19), 12 th grade/HS Graduate (31.7%, n=64), GED (7.4%, n=15), some college (31.2%, n=63), AA/AS (5.4%, n=11), BA/BS (6.4%, n=13), MA MS (2.0%, n=4), PhD (0.5%, n=1), and Vocational (1.0%, n=2). Specifically, most probationers in the sample graduated high school and had some college 21 With regard to employment, most participants were either employed full time (38.1%, n=77) or not emplo yed (28.7%, 21 This is an interesting finding for the particular sample, as the data was collected in a city that is in close proximity to a university. Because of this many of the individuals in the sample could have been college students who were on probation. This could have also affected the age range for the current sample. While the current instrument did not specifically ask probationers to indicate if they were a student (as it was not anticipated that there would be a higher magnitude o f students on probation) during interviews many identified as students. This issue will be expanded on in the limitations section

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84 n=58). Some were employed part time (18.3%, n=37) or self employed (1.5%, n=3), others identified as being a student (5.4%, n=11), and homemaker (0.5%, n=1). We also had some who indicated being disabled (5.9%, n=12) or retired (0.5%, n=1). Whe n looking at marital status of probationers who participated in the study, most were never married (51%, n=103), with others reporting being married (13.4%, n=27), divorced (19.8%, n=40), separated (6.4%, n=13), or living with a partner (8.4%, n=17). In te rms of children, most participants had children (60.4%, n=122). Moreov er, current offense history was obtain both through self report and from official records. When looking at probationer s self reported current o ffense characteristics (Table 4 2) proba tioners were able to indicate the length of their sentence, time served, and whether or not they received their sentence as a result of a plea agreement (Table 4 2). With regard to sentence length, self report indicated probationers serving from 3 months t o 36 months. Mo st indicated serving a 12 month sentence on probation (69.3%, n=140). At the time of the interview participants also indicated the length of time that they had served on their probation sentence at the time of the interview. Most stated that they had served 1 to 3.5 months (30.2%) and 4 to 6 months (43.1%, n=87), however some did indicate having served 10 to 18 months at time of interview (8%, n=16). In terms of plea bargaining, 74.3% identified as having plea bargained for the current charge With regard to current offense characteristics obtain from official records, sentence length, current offense type, and number of charges are discussed. In terms of sentence length, o fficial records indicated probationers officially serving 6 months (14 .9%, n=30), 9 months (1.0%, n=2), or 12 months (84.2%, n=170). Although there

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85 were differences between official records and self report, both indicated that a majority were serving 12 month sentences. While participants were on probation for a myriad of of fenses, most probationers who participated were on misdemeanant probation for a public ordinance violation/offense (60.4%) followed by violent offenses (21.8%), property offenses (10.4%), and drug offenses (7.4%). Most offenders were currently on probation after being charged with one offense (78.7%, n=159). However, there were some offenders who had multiple charges. Although most only had one current offense they were being charged with, some had 2 offenses they were charged with (15.8%, n=32), 3 offenses (3.9%, n=8), or 6 offenses (0.5%, n=1). Official criminal h istory NCIC/FCIC and Court Services county Databases LINDAS and Monitor. Cri minal histories ranged (Table 4 3) some had very limited official criminal histories, including those with no previous adult criminal history (28.7%, n=58) (i.e. this current probation sentence was their first offense so they had no previous criminal history). Most however, had a previous adult criminal history (71.3%, n=144), many of which had extensive criminal histories that included felony and misdemeanor offenses, records of incarceration to both jail and prison facilities. Most did not have a juvenile record present (91.1%, n=184). Specifically, 30.7% had a violent/persons offense present, 42.1% had a previous property offense, 34.7% had a previous drug offense, and 58.4% had a previous public ordinance offense present on their criminal history. Official criminal history data (rathe r than self report) was used in the current analysis for offense history. This approach was taken due to the fact these this data were more complete and researchers felt it to be a more accurate depiction of

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86 probationers offending patterns than the self report data, where some probationers seemed to be hesitant to admit to participating in such offenses. Such participants appeared to need some reassurance while completing the interview, which researchers provided to all inmates throughout the interview p rocess (because of the nature of their sentence and their status as a probationer) 22 Three different offense variables were created for analysis (Table 4 4), a seriousness scale, a diversity measure, and offense types as dummy variables). Based on the seri ousness scale (which ranges from 0 to 15, higher scores indicate more serious offenders, lower scores indicate less serious offenders based on the degree and level of the offenses they have perpetrated), descriptive statistics indicate that most offenders are less serious offenders, with a mean of 3.56. The diversity measure, which ranges from 0 to 3 (high scores indicating a more diverse offender, or participating in more types of offending), has a mean of 1.50. This may indicate that offenders are more s pecialized in the types of crimes that they choose to commit rather than participating in a range of crime or criminal behavior 23 When looking at each type of offender (the dummy coded variables by type of offense, all range from 0 to 1, where 0 indicates no history for that type of offense 22 Both self report and official data were collected so that researchers could have the most complete view of their offending h istory and better capture the extent of crime probationers have engaged in. Sometimes, self report data has proven to be an important tool in helping researchers capture or get closer to the true amount of crime (as it helps us see not only crimes committe d where official CJ intervention occurred, but also those offenses where probationers may not have been caught) (Maxfield & Babbie, 2008). However, researchers also recognized some of the issues and limitations associated with self report data (i.e. issues with the validity of the data based on how truthful probationers are willing to be and whether or not they over or under report). While researchers note that offending populations tend to provide accurate data with regard to offending (Peterson, Braiker, Polich, 1981) and used techniques to increase truthful self reporting (i.e. ensure and offer confidentiality, have then report this information in a private room away from probation staff) some participants seemed to need reassurance (which researchers pro vided). As such, researchers determined that official records data would be most appropriate here. 23 However, this does not imply that they do not participate in a range of criminal behaviors within each type. This only indicates that participants are committing the same types of offenses.

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87 present and 1 indicates the presence of that particular offense type) we see that drug offending, has a mean of .486, property offenders has a mean of .590, violent offenders has a mean of .431, and public ordinance has a mean of .819. Generally speaking, there are more offenders with public ordinance crime present in their criminal history than any other crime type. Self r e port criminal h istory Although researchers had access to official criminal records, in an effort to capture both crimes that they have been officially processed for and those that they have not been, we collected self report data on offending. Researchers asked participants if they had participated in 21 different offenses during their semi structured interviews. These crimes included property, drug, and violent offenses. While most probationers denied participating in many of the listed offenses, there were some offenders who did admit to certain crimes. Whi le research has shown inmates often provide accurate self report of their past offending history (Peterson, Braiker, & Polich, 1981), we anticipated that some offenders might be less willing to admit to their offense history because of the nature of their sentence (i.e. being on probation) Due to t he fact that probationers are serving their sentence in the community, some might have felt as if admitting to many of the offenses listed would lead to a violation. But again, researchers reassured them at every stage of the interview process that the sur vey was confide ntial. Results showed (Table 4 5) that probationers were most likely to report drug possession (48%, n=97), dealing drugs (24.8%, n=50), harassing someone (31%, n=62), and to beating up/assaulting someone (37.12%, n=75). Probationers also a dmitted to threatening someone with out a weapon (14%, n=28), breaking into

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88 attacking someone with a weapon (10%, n=20), stea ling a car (6%, n=12), robbing someone (4%, n=8), vanda breaking in (10.4%, n=21), committing a home invasion (1.5%, n=3), drive by shooting (2%, n=4), carjacking someone (1%, n=2), and participating in gang (4%, n=8). Social d isorganization Participants were asked several theoretically driven questions to obtain measured using three scales and two additional variables. Two scales included perceptions of physical and social disorder, both ranged from 1 (not a problem) to 4 (a big problem). Higher scores on the scale indicate higher levels of disorder and lower scores indicate lower le vels of perceived disorder. The third scale used to measure perceptions of social disorganization was collective efficacy (with response options ranging from 0 to 1, where a 1 indicates the presence of collective efficacy and 0 indicates a lack of collecti ve efficacy). The other two neighborhood items were subcultural diversity (ranged from 1 to 3, where higher scores indicate higher levels of diversity), and residential mobility (ranged from 1 to 3, where higher scores indicate greater mobility). Results show (Table 4 6) that most participants did not indicate perceptions of high social disorganization in their communities. On average, participants indicated low perceived social and physical disorder, living in a community with collective efficacy present, with medium levels of residential mobility and subcultural diversity. Specifically, social disorder had a mean of 1.5. Physical disorder had a mean of 1.39, Collective

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89 efficacy had a mean of .813, Subcultural diversity had a mean of 2.11, and residential mobility had a mean of 1.82 Dependent Variables: Fear of c rime Participants were asked about their fear of several different crimes. Specifically, they were asked about 2 1 different crimes (see Table 4 7). Recall that t hese were combined into three scal es and one additional variable by offense type, including fear of violent/persons crime, property crimes, and drug crimes and a general fear of crime scale. 24 Results indicate that most participants did not experience high levels of fear of crime generally or of any of the specific offenses. Specifically, descriptive statistics for the indices show fear of violent crimes had a mean of 2.41, fear of property crime had a mean of 2.15, and fear of drug crimes had a mean of 2.11. Generally, probationers did no t indicate having high levels of fear across all fear types that is, they were somewhat afraid. However, they did indicate being slightly more fearful of violent crimes than property or drug crimes. When looking at the specific items that make up each of the fear of crime scales, a s imilar pattern emerges (Table 4 8), with most responses having a mean around 2. On average, probationers indicated feeling somewhat afraid or afraid for each crime aske d during the interview (Table 4 9). For example, they indi up or being attacked without a weapon. 24 To create the scales, I added the fear of crime items and then divided by the number of items being combined. Response options ranged from 1 (not afraid) to 4 (very afraid), where higher scores indicate higher fea r levels

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90 Altruistic f ear Probationers were also asked about altruistic fear, which is fear for one s family and oth ers. The participants in the present study are offenders, and their criminal involvement could possibly put their families in danger (or participants may live in areas that are conducive to crime and victimization). We wanted to see if they had fear for t heir family, and if so who m The first variable asked probationers to compare fear for themselves v. their family members (so it is asking them to determine who they have higher fear levels for family or their own personal fear). To allow an examination o f fear for each type of family member, there were 6 separate variables (fear for mother, father, husband, wife, son, and daughter) for each type of family member, which will all be analyzed separately. Due to the fact that the number of cases for each of these variables is small, rather than conducting regression analysis, we explored altruistic fear among probationers by examining descriptive statistics. With regard to probationers fear for themselves compared to their family, genera l are you more, less, or equally afraid for other 3, where 1 is coded as more afraid, 2 is coded as less afraid, and 3 is coded as equally afraid. This was recod ed so that it is in the same direction as the other variables in the study. So not 1 is coded as less afraid, 2 is coded as equally afraid, and 3 is coded as more afraid, so that higher scores indicate higher levels of fear for their family compared to the mselves and lower scores indicate lower levels of fear for their family in comparison to themse lves. Results indicate (Table 4 10) that most probationers are more afraid (49%, n=99) or equally afraid (33.2%, n=67) for their family member as they were for t hemselves, with a mean of 2.31.

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91 When looking at specific family members, probationers were asked how fearful they were for the following family members that they lived with 25 : Father, Mother, Husband, Wife, Son, and Daughter. Response options ranged from 1 (coded as not afraid) to 4 (coded as very afraid), where higher levels indicate greater fear of crime for each of these family members and lower levels indicate less fear of crime for each family member. Due to the fact that participants may not live or b e in contact with some of these family members (and therefore may not have any feelings of fear for such individuals) t he current analysis focuses only on family members who were living with the participant at the time of the survey. With regard to fear for one s parents, only 54 probationers indicated liv ing with their fathers (Table 4 11), of those 54, most indicated being somewhat afraid for their fathers (mean of 1.78). Many probationers indicated living with their mother (n=79), however, many were so mewhat afraid for them (with a mean of 2.05). When looking at one s spouse, only 22 participants indicated having a husband, and most were not afraid for them (with a mean of 1.59). Similarly, only 27 participants indicated having a wife with whom they liv ed. They generally were somewhat afraid for them, with a mean of 1.85. With regard to one s children, 70 probationers indicated having and living with a son. Interestingly, most probationers who indicated living with a son, indicated they were either somew hat afraid (n=18, 25.7%), afraid (n=8, 11.4%) or very afraid (n=22, 31.4%) for them, with a mean of 2.43. When looking at daughters, 61 probationers indicated having and living with a daughter. Consistent with prior research (Warr & Ellison, 2000), most in dicated having some level 25 So only those who indicated living with each of the six family members answered how fearful they were. Descriptive findings in this section are only for those probationers who indicated they lived with that family member.

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92 of fear for their daughte r, with a mean of 2.62 (Table 4 10). Of the 61, who lived with a daughter, 21.3% (n=13) said they were somewhat afraid, 11.5% (n=7) said they were afraid, and 39.3% (n=24) said they were very afraid for th eir daughters. Due to the fact that much of the data was highly skewed, these variables were then coll apsed and dichotomized. Table 4 11 shows the descriptive statistics of these variables after being collapsed. Each of the six variables were dichotomize d, so that 1 (not afraid) is coded as 0 (not afraid) and those who answered 2 (somewhat afraid), 3 (afraid) or 4 (very afraid) were recoded as 1 (afraid). Descriptive statistics (Table 4 11) reveal that for those who indicated they lived with each type of family member, participants were more likely to say they were not afraid for their mother, fat her, wife, or husband. Many participants also indicated being afraid for their son or daughter (specifically, most indicated being fearful for their son, n=70) S o of those probationers who indicate living with a family member, it seems that those probationers who were afraid were afraid for their children (and are not as fearful for parents or spouses). To examine the role of gender and altruistic fear, simple c ross tabulations were conducted. Findings show that with regard to fear for others compared to their own fear, of the seventy four female probationers, 41% (n=30) indicated being equally afraid and 42% (n=31) indicated being more afraid for others. Interes tingly, most males indicated being more afraid for others (54%, n=68). Fewer reported being equally afraid (n=37, 30%) or less afraid (n=23, 18%). Moreover, of those who indicated living with their father, both male and female participants most often repor ted being not afraid for them. Of those who did, there were more males who indicated fear (n=14) than female participants (n=8). With regard to probationers mothers, by a small margin, more

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93 females indicated being fearful for their mothers (n=18) than not (n=14). Males indicated more often to not be afraid for their mothers (n=26) than afraid (n=21). With regard to spouses, of the women who indicated living with their husband, 72.7% (n=16) indicated being not afraid for them. Interestingly, males who indica ted living with their wives (n=27), most reported not being afraid for them (55.6%). Finally, with regard with ones children, of those who indicated having a son (n=70), both males and females indicating having fear for them more often than not. So 60% (n= 18) of women (of 30 who reported having a son) reported being afraid for their son. With regard to the 40 male participants who had a son, 75% (n=30) reported being afraid for their son. For those who said that they had a daughter that they lived with, a similar pattern emerges. Of the 29 females that indicate having a daughter, 70% (n=20) report being afraid for them. Similarly, male participants who indicate having a daughter they live with (n=32), most report being afraid for them (n=24, 75%). Overall we were able to find some support for hypothesis 4. Through descriptive analysis, we were able to determine that there are some offenders who are fearful for their family members. Most probationers noted being fearful for their son (n=22, 31.4%) or d augh ter (n=44, 72.1%). Table 4 1 1 also indicates that some probationers were fearful for their mother or father. In both cases, there were more probationers indicating fear of for female family members (daughters, mothers, wives) than males. Few indicated bein g fearful for their spouse. Finally, when asked how afraid they were for family members compared to them, most probationers indicated they were more fearful for others (n=99, 49% more afraid). Some also indicated to being equally afraid for family as they are for themselves (n=67, 33.2%) and few indicated being less afraid for

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94 family (n=36, 17.8%). This is interesting, here we can see that most probationers hold some level of altruistic fear and it seems to be higher for female family members. Moreover, it seems that female offenders tended to report being more fearful for others. Male participants also reported being fearful for other family members. Pr ecautionary b ehaviors Probationers were asked about the types of precautionary behaviors they particip ated in to protect themselves from them from being victimized. Probationers were asked if they participated or engaged in 10 different precautionary behaviors. These items were placed into three scales (which were created by adding the items together and t hen dividing by the number of items in the scale see methods section for further detail). The three scales include avoidance behaviors, defensive behaviors, and target hardening behaviors. Response options ranged from 0 to 1, so those who indicate a 1 en gaged in the specified behavior and those who indicate a 0 do not. In general, probations were more likely to participate in avoidance behaviors. Few indicated using defensive behaviors or target hardening behaviors to protect themselves from being victimi zed. Specifically, resul ts for each scale show (Table 4 12) defensive behaviors with a mean of .231, avoidance behaviors with a mean of .457, and target hardening behaviors with a mean of .293. Within each scale, descriptive st atistics for each item (Tabl e 4 13) also show similar results. With most participants indicating that they participate in avoidance behaviors and few indicated engaging in any defensive or target hardening behaviors. Quantitative and Qualitative Data Analysis Findings This section pr esents the results from the data collected from the 202 semi structured interviews conducted on misdemeanant probationers. Findings from the

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95 multivariate analysis (that examine the relationships for each of the four research questions mentioned earlier) wi ll be presented and discussed in detail. Due to the fact that there are many models being examined, this section will be separated by research question (rather than by model), where quantitative models and qualitative findings will be discussed. Personal Fear of Crime Research q uestion 1 and 2 Are more serious offenders less fearful of crime? If so, what types of crime? How do perceived neighborhood characteristics affec t probationers fear levels for themselves? Four theoretically driven step wise multivariate liner regressions were estimated to social disorganization characteristics in their neighborhoods for each of the four dependent variables. These dependent variables were: general fear of crime,, fear of violent crime, fear of property crime, and fear of drug crime (Table 4 14). All three scales range from 1 to 4. This section is presented in four tables (for each type of fear being predicted), where independent variables vary across steps. Predicting general fear of c rime Tab le 4 14 shows the Ordinary Least Squares (OLS) step wise regression predicting general fear of crime for the full sample. Specifically, demographics, offense general fear of crime. All four models were statistically significant overall (F statistic was significant at the .001 alpha level).

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96 Step 1 (or model 1), which includes only demographic control variables (age, race, and gender) explained 11.8% of the variance in general fear of crime ( R 2 = 118). The variables in step 1 were examined individually to see what effect a change in race, found to be statistically significant: race (at the .01 alpha level) and gender (at the .001 alpha level). Age was not found to be a significant predict or of general fear of crime in step 1 Specifically, gender had a negative relationship with general fear of crime, so females were significantly more likely to experience general fear of crime than men. Step 2 (Table 4 14) added the offense history of pr obationers to the step wise regression; however, none of the offense history variables were significant. This means that the type of offense history a probationer had (including violent, drug, property, and public ordinance offense as well as a CH seriousn ess scale) did not have a significant effect in predicting general fear of crime. So the type of offending history and the he offense seriousness scale was not statistically significant, it was inversely related to violent fear of crime so less serious offenders were more fearful of crime as anticipated. However, gender and race remained significant after including offense h istory variables. Similarly, as in step 1, women and non whites were significantly more likely to be fearful. The addition of offense history variables also helped explain more variance (about a 2% increase) in general fear of crime (13.8% or an R 2 of .138 ). Step 3 added the current offense of probationers, which included violent, drug, property, and public ordinance offen ses. Again, as shown in Table 4 14, offense history

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97 did not have a statistically significant effect. This means that offense history has no variables, race is no longer a significant predictor of general fear of crime. Variables that remained significant predictors included: gender (at the .001 alpha lev el), property (at the .05 alpha level), and public ordinance (at the .01 alpha level) offenses. So here we can see that females are still significantly more likely to be fearful than males (b coefficient = .551) and those whose current offense is a proper ty crime are more likely to be fearful than those who are violent offenders (b coefficient = .680). Interestingly, public ordinance offenders were found to be less likely to experience general fear of crime than those who committed a violent offense (b coe fficient = .338). With the variance in general fear of crime (R 2 = .182). Step 4 (Table 4 14) added social disorganization variables (including social and physical disorder, collective efficacy, residential mobility and subcultural diversity). The overall model, which included all variables, explained 20% of variance in general fear of crime (R 2 = .200; this is an 8.2 % increase from the first model). In the final s tep, females continue to experience significantly more general fear of crime than males do (at the .001 alpha level). Race and offense history are not significant predicto rs in the final model. Current property offender (at the .01 alpha level) and public ordinance offenders (at the .05 alpha level) were still significantly less afraid than violent offenders. As shown in Table 4 14, collective efficacy was the only significant predictor among the social disorganization variables of general fear of crime. In terestingly, collective efficacy was positively related to general fear of crime, so the more collective efficacy perceived

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98 by probationers the more general fear of crime they expressed. While this is not consistent with what the researchers theoretically hypothesized (as many like Gibson, et al., 2002, have found increased levels of collective efficacy to lead to lower levels of fear, this relationship has been found in other studies on fear of crime among offenders (such as Lane & Fox, forthcoming and Rom an & Chalfin, 2008). For example, Roman & Chalfin (2008) found similar results, where higher levels of collective efficacy were related to higher levels of fear. They argue d that in neighborhoods where there are high levels of crime or where crime tends to be pervasive, the amount of community cohesion among neighbors may not matter. R oman & Chalfin (2008) also noted that the presence of collective efficacy among neighbors can result not only in an increase in neighbors coming together to combat crime but c an lead to an increase in the dissemination of information on crime and violence in their community, which in turn can result in higher levels of fear. Suggesting that collective efficacy among neighborhoods with higher perceived crime may magnify the pres ence and impact of crime in ones neighborhood and thus fear that such individuals have (Roman & Chalfin, 2008). Overall, female participants were found to be significantly more fearful than males, across all four steps. This is consistent with past resear ch, which finds that women tend to be generally more afraid of crime (Ferraro, 1995, Ferraro & LaGrange, 1992, Lane & Meeker, 2003; Lane, Gover, & Dahod, 2009, Warr, 1984). Non whites (including blacks and Asians) were found to be significantly more afraid than whites until the third and fourth step, where current offense and social disorganization variables were added to the analy sis. With regard to probationer s current offenses, only those charged with a property crime were more afraid than violent offen ders. T hose who were not charged

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99 with ordinance offenses experienced less general fear of crime than violent offenders With regard to the neighborhood probationers live d in, it seems that collective efficacy mattered the most, but not in the way that rese archers anticipated it would. Findings demographic characteristics, those probationers who felt or perceived higher levels of collective efficacy experienced more gene ral fear of crime. Lane & Fox (forthcoming), who examined a similar offending population (jail inmates) found a positive relationship between collective efficacy and fear of prope rty crime. They argue that it is possible that those who live in areas where collective efficacy is greater, such as those neighborhoods that are nicer or more affluent in terms of income, may generally worry more about crime because they have a fear of losing their property. I think that this same rationale can be expanded to the current study. It may be that because many of those interviewed were on probation for low level offenses (mostly public ordinance offenses like DUI) and may come from nicer communities they generally experience higher levels of fear because they have more to lose from if they are victimized. So with regard to general fear of crime, prior offense history does not seem to have a significant hypothesis was supported in the dire ction of the relationship (the seriousness of past criminal offenses committed was negatively related to general fear of crime), this was not a significant predictor of general fear of crime in any of the four models estimated. What seems to matter most is experience general fear) and current offense (specifically, whether or not there current offense was a property or public ordinance offense compared to a violent offender ). The

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100 property offense resul ts are in agreement with what we originally hypothesized, that less serous offenders (such as those who commit misdemeanant property crimes) would be more likely to be afraid of crime than violent or more serious offenders. In terms of neighborhood effects direction). While we anticipated and found a positive relationship between perceptions of disorder, subcultu ral diversity, and residential mobility and general fear these variables were not statistically significant predi ctors of general fear of crime. Predicting fear of violent c rime Table 4 15 shows the series of OLS step wise regressions estimated to predi ct fear of violent crime among probationers. All four models were found to be statistically significant (as denoted by the F statistic, which was significant at the .001 alpha level). Similar to the series of regressions above predicting general fear of crime, gender was significant throughout all four steps in predicting fear of violent crime. Specifically, step 1, where demographic predictors were included alone (including age, race, and gender), both gender (at the .001 alpha level) and race (at the .0 1 alpha level) were statistically significant predictors of violent fear of crime. So women (b coefficient of .515) and non white (b coefficient of .417) probationers were found to be more likely to report fear of violent crime. Here demographics alone e xplain about 10.4% of the variance in fear of violent crimes (R 2 = .104). Step 2 (Table 4 property, and ordinance offense histories). We also add offense seriousness scale. The addition of s uch variables increased the explained variance to 12.6% (R 2 = .126), which is a modest 2.2% increase or change in variance explained. None of the offense history

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101 variables were significant when added to the model. However, expected relationships were found and consiste nt with the findings in Table 4 14. The offense seriousness scale was negatively related to violent fear of crime, so the more serious the offender the less fear of violent crime they experienced (but was not a statistically significant variab le). Gender and race remain to be significant predictors and the .001 and .01 alpha levels, respectively. Similar to the findings in the previous step wise regression for fear of crime generally, women and non white probationers are significantly more lik ely to experience fear of violent crime. Step 3 (Table 4 15) adds current offense to the series of regressions (which include drug, property, and public ordinance current charges violent offense was the reference category ). The addition of such variable s increased the variance explained to 17.1% (R 2 were not found to be statistically significa nt. So the types of offenses and offense histories offenders have do not have a signi violent crime in this sample. Similarly, the seriousness of the offenses committed by once current offense is included i n the model race is no longer a significant predictor. The only two significant predictors are gender (at the .001 alpha level) and property offenses as a current charge. So it seems that females, again tend to be more fearful of violent crimes as well as those who are charged with property offenses (compared to those who were charged with a violent offense). Finally, as seen in Table 4 15, step 4 adds social disorganization variables to the model. Once added to the model, the variance explained in fear of violent crime

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102 increases to 18.7% (a 1.6% increase in explained variance and a 8.3% increase in variance explained from step 1 (where only demographics were present) to step 4 where demographics, offense history, current offense, and social disorganization are accounted for. When social disorganization variables were added to the model, offense history remains non significant, as does age and race. Gender, however, continues to be significant (at the .001 alpha level; b coefficient of .602). So it seems th at once all variables are accounted for (offense history, neighborhood perceptions, and current charges) women still continue to have a significantly higher likelihood of being fearful of violent crime. This is similar to the findings for general fear of c rime; there is something about gender specifically female probationers that leads them to be more likely to be fearful of violent of crime and crime more generally. O verall, across all four steps (Table 4 15 ) women were significantly more fearful of vi olent crime than men. Age seems to only matter until current offense is accounted for. Only those with a property charge as a current offense were found to be significantly fearful of violent crime. This remains significant even after perceptions of socia l disorganization were accounted for. It seems that being a women and being on current probation for property charges are the two most consistent predictors of fear of violent crime (and gen eral fear of crime as shown in Table 4 14). In comparison to the r egressions predicting general fear of crime, where collective efficacy was significant in predicting general fear of crime, it is not a significant predictor for fear of violent crime. Also, public ordinance current charges were not significant predictors of fear of violent crime, but were significant in predicting general fear of crime. With regard to research

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103 of violent crime (or general fear of crime as discussed a bove). Similarly, while the direction of the relationship for offense seriousness was consistent with what researchers hypothesized (negatively related to fear of violent crime) it does not have a Current offenses, specifically property charges, do matter. So those probationers who were charged with property offenses are significantly more likely to report or experience fear of violent crime than violent offenders were R esearchers expected more ser ious offend ers to be less fearful of crime Finally, neighborhood perceptions were not significant predictors of fear of violent crime, which was not anticipated by the researchers Pr edicting fear of property c rime In order to examine the relationship betw fear of property crime, Table 4 16 shows the OLS step wise regressions that were estimated. All four models were statistically significant at the .001 alpha level. Step 1 here includes demographic variables (age, race and gender). As seen with the two previous step wise regressions predicting general fear of crime (Table 4 14) and fear of violent crime (Table 4 15), gender and race are both statistically significant predictors of fear of property crime. So non whites (blacks and Asians) are significantly more likely to be fearful of property crime at the .05 alpha level (b coefficient = .231). However, this is not as strong of a predictor for fear of property crime as it was found to be for fear of violent crime and g eneral fear of crime. Also, gender was a found to be a significant predictor of fear of property crime. So again as we saw in Table 4 14 and 4 15, females were significantly more likely to report fear of property crime than male probationers were. Demogra phic factors alone can account for 12.4% of the variance in fear of property crime (R 2 = .124).

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104 Step 2 adds offense history variables, which accounts for the different types of offense histories that probationers may have, including violent, drug, propert y, and public ordinance offenses. Step 2 also includes offense seriousness scale to account for such variables only increases the variance explained minimally, with 1 3.6% of the variance in fear of property crime explained (R 2 = .136), because none of them are significant predictors. However, gender (b coefficient of .507) continues to remain significant in the second model. In fact, after offense history variables are added, the strength of the relationship between gender and fear of property crime increases. So females continue to be significantly more afraid of property crime (at the .001 alpha leve l) than males (as was found in Table 4 14 and 4 15 predicting gene ral fear of crime and fear of violent crime, respectively). Non whites, meaning black, Asian and Hispanic probationers, also are still more likely to indicate fear of property crime than white participants (b coefficient of .273) at the .05 alpha level. Step 3 (Table 4 16) adds current offense to the model, accounting for the charge for which probationers are currently serving a probation sentence. This inclu des charges that are categorized as violent, drug, property, and public ordinance offenses (violen t offenses serves as the reference category) Once current offense is added to the model race is no longer significant. Gender, again remains significant and the streng th of the relationship increased as well (b coefficient of .511). Here again, women con tinue to be more fearful of property crime than men. So we see the same pattern emerge with gender as in the previous models predicting fear of property crime and in the series of models predicting general fear of crime (Table 4 14) and violent fear of

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105 cri me (Table 4 15), even after accounting for offense history and current charge. Again, property offenders were more afraid of property crime than violent offenders were. The overall model can explain about 16.9% of the variance in fear of property crime (R 2 = .169). The final model (step 4) adds social disorganization variables, accounting for mobility, and subcultural diversity in their neighborhoods. After adding in these variables, the amount of variance explained in fear of property crime increases to 19% (R 2 = .190). So we can see that as we account for demographic factors, offense history, current offense, and neighborhood perceptions, we can explain about 6.6% m ore of the variation in fear of property crime. Although none of the social disorganization variables were significant predictors of fear of property cr ime (as found in Table 4 15 as well when predicting fear of violent crime), gender (b coefficient of .5 29) and current property offense (b coefficient of .521) remain as the only two significant predictors for fear of property crime. Specifically, we can see in Table 4 1 6, that female offenders are still significantly more likely to experience fear of prope rty crime and those who are currently on probation for property offenses experience fear of property crime more than thos e who are on probation for violent charges. With regard to the research questions of interest, it seems that even after accounting for offense history type (so if they are a violent offender compared to a property offender or drug offender) has no effect on their fear of property crime. The seriousness of the offenses com mitted by probationers also does not have a significant effect on their fear

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106 of property crime. The only consistently significant predictors for fear of property crime are gender so if you are a female you are more likely to experience such fear and if you have committed a property offense. This is consistent with the previous set of analyses predicting fear of violent crime (Table 4 15). It could be that females who are charged with property offenses feel that because they are involved in such a lifest yle they may have a higher risk of similar victimization. Also, in terms of perceptions of neighborhood influences on fear of property crime, it seems that none of these factors mattered in predicting their fear of property crime. Predicting fear of drug c rime The final set of step wise regressions estimated work to predict fear of drug crimes (which includes being around drug sales or around the growing/m anufacturing of drugs). Table 4 17 shows all four models to be significant (as noted by the F statisti c, probability <. 001). Step 1 includes only the demographic variables of probationers (including race, age, and gender). Interestingly, this is the first model to show age as a significant predictor of fear, specifically here for fear of drug crimes. In the above models predicting general fear of crime (Table 4 14), violent fear of crime (Table 4 15), and property fear of crime (Table 4 16), age was not a significant predictor. So here, the older the offender the fearful they are of drug crimes. This coul d be due to older individuals feeling a greater sense of vulnerability to their person when drug crimes occur around them. Yet, the magnitude of this effect is quite small (b coefficient of .020). Race and gender were also found to be significant predicto rs of fear of drug crime. Women (as found in the previous models) are significantly more likely to be fearful of drug crimes (b coefficient of .616, significant at the .001 alpha level) and non whites are also more

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107 likely to be more fearful of drug crimes than whites (b coefficient of .376, significant at the .05 alpha level). Step 2 adds offense history to the model. The only type of offense history that seems to matter in predicting fear of drug crime is a public ordinance offense (at the .01 alpha lev el, b coefficient = .664). This is the first model that any offense history has been found to be significant. So those with a history of public ordinance offenses are more likely to indicate fear of drug crime than probationers who do not have a history of these offenses. However, the offense seriousness does not matter. The addition of offense history helped explain more variance in fear of drug crime, explaining 17.4% of the variance (R 2 = .174). Furthermore, a ge and gender of the participant still matter but race drops out and no longer matters in terms of predicting fear of drug crime. So we still find that those who are older experience greater fear of drug crime (b coefficient .016, .05 alpha level). However, the magnitude of this effect is very small Also, females still have a significantly higher likelihood of being fearful of drug crime than men (b coefficient .733, .001 alpha level), which is consistent with what we fo und in the first model (Table 4 17) and in the first three series of step wise regressions predicting general fear, fear of viol ent and property crime (Table 4 15 and 4 16, respectively). Step 3 (Table 4 17) as before, adds current offense variables. However, unlike in the previous regression models predicting general fear of crime, violent fear of crime and property fear of crime, none of the types of current offense charges matter (i.e. they are not significant predictors of fear of drug crime). Moreover, when looking at gender, females are still more likely to experience fear of d rug crime and older offenders are also more likely to experience fear of drug crime. With regard to offense history,

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108 probationers who have a public ordinance offense history are more likely to experience fear of drug crimes than those who have other types of offense history. Again this could be due to the fact that public ordinances offenses tend to be non violent in nature. So while researchers anticipated offenders would not be very fearful, we expected that those offenders with non violent criminal histo ries would be more fearful than those with violent histories (Lane and Fox, 2009 argue in their piece on fear among jail inmates). Interestingly, offense seriousness still does not have an effect in predicting fear. With current offense variables being add ed to the model, 19.1% of the variance in fear of drug crime is explained (R 2 = .191). In t he final model, step 4 (Table 4 17), social disorganization variables were added and increased the explained variance to 22.1% (R 2 = .221). We see similar findings with the previous models in predicting fear of drug crimes. Women are significantly more likely to experience fear of drug crime than men (b coefficient of .746, .001 alpha level) and older probationers are more likely to be fearful of drug crime than you nger probationers. However, the magnitude of this effect is still very small (b coefficient of .016). Probationers with a history of public ordinance offenses are also still more likely to be fearful of drug crime than probationers who have other criminal history patterns. As with previous regressi ons predicting violent (Table 4 15) and property (Table 4 16) Overall, females seem to be significan tly more likely to be fearful of drug crime across all four models. Across all models, older probationers are also more likely to experience such fear (than those on probation who are younger). The only type of

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109 offense history that seems to matter is publi c ordinance offense history, which is ious offenders are more afraid. Also race only seems to matter in predicting fear of drug crime until we account for offense history Summary of Findings for Personal Fear of Crime Overall, women seem to be significantly more fearful than men. Specifically, women were more likely than men to express ge neral fear of crime (Table 4 14), fear of violent crime (Table 4 15), fear of property crime (Table 4 16 ) and fear of drug crime (Table 4 17). This held consistent even after controlling for offense history, current offense, and neighborhood perceptions in all four series of step wise regression models. In terms of race, non whites seem to experience more fe ar than whites; however, when all variables were accounted for this effect dropped out for all four types of fear. Age was only significant in predictin g fear of drug crime (Table 4 17). OLS regressions revealed that older offenders tend to be more fearful of drug crimes, after accounting for neighborhood perceptions and offense history. In terms of offense history, it seems that seriousness of offense generally does not matter. So research question 1 (which expected that less serious offenders would be mor e afraid) is not supported. It may be possible that wit h a larger sample or a sample including felony probationers (rather than low level misdemeanant probationers) some significant findings may emerge. Only when predicting fear of drug crimes were probati oner s significant. Holding all other variables constant, probationers with a public ordinance offense history are more fearful of drug crimes than probationers who did not have this history. This is consistent with what researchers antic ipated. Researchers hypothesized that offenders in general would be reluctant to report being fearful of crime. However, we also

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110 hypothesized that non violent offenders would be more fearful than violent offenders. Due to the fact that public ordinance off enses are non violent in nature, it was expected that those with public ordinance offense histories would be more fearful. However, we expected they would be fearful of violent crimes rather than non violent crimes. So it is interesting that it is only sig nificant for fear of drug crime, but it may be because this is the type of crime they have the most experience with in their lives. In terms of current offense, probationers charged with property offenses were more likely to experience general fear of crim e, as well as violent fear of crime. Those with current charges that were public ordinances were more likely to have general fear of crime. Overall, it seems that offense history and current offense are not as significant in predicting fear of crime as was originally anticipated. However, future exploratory work should be conducted to see if offenders in different settings or with different correctional sentences (i.e. jail inmates v. probationers, v. those on parole, etc.) produce similar findings. Finally neighborhood perceptions seem to only matter when predicting general fear of crime. Interesti ngly, as noted above in Table 4 14, the only neighborhood variable that was significant was collective efficacy and it had a positive relationship with general f ear of crime. While one would not anticipate that those who live in areas that they perceive to have a higher likelihood of collective efficacy (meaning in areas where there are informal social controls in place and feel like they can trust their neighbors or trust that they will do something if crime occurs or kids misbehave) to be more fearful, this is not the first study to find this result. Lane & Fox (forthcoming) had similar findings among offenders in jail. So it might be that those on probation who live in nicer areas may feel like they have more to lose or might see themselves as being more vulnerable to

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111 victimization. In terms of research question 2, it seems that neighborhood perceptions only mattered when predicting general fear of crime and do n ot have a significant effect in predicting fear of violent crime, fear of property crime, or fear of drug crimes, when they are examined individually. Precautionary Behaviors Research q uestion 3 : What precautionary behaviors do probationers take part in to cope with personal fear of crime? Are more serious offenders likely to use defensive behaviors (defensive vs. avoidance behaviors)? Three series of step wise logistic regression models were estimated predicting the precautionary behaviors that misdeme anant probationers use to protect themselves. Precautionar y behaviors are broken into three separate series of analysis, where the use of defensive beha viors (Table 4 18), of avoidance behaviors (Table 4 19 ), and targ et hardening behaviors (Table 4 20) are predicted separately. Due to the fact that present analysis is using binary dependent variables with dichotomized outcomes (0/1), logistic regression is the most appropriate way to examine the effect of the independent variables on the dependent variables (Long & Freese, 2006). This section presents the results from the step wise logistic regression analysis predicting the use of defens ive precautionary behaviors, avoidance precautionary behaviors and target hardening precautionary behaviors. Results are presented in Table 4 18, 4 19, and 4 20 ( one for each type of precautionary behavior being predicted), where independent variables vary.

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112 Predicting defensive p reca utionary b ehaviors The step wise logistic regression models were estimated by incorporating new independent variables of interest i n each step. As seen in Table 4 18, here were five steps (or models) run, where step 1 included the control variables (demographics) only, step 2 added offense history of the probationers (violent, drug, property, an d public ordinance offenses and a offense seriousness scale). Step 3 added measures of probationers current charge (drug, property, and public ordinance offenses with violent offense charges being the reference category), step 4 included measures of perc eived social disorganization (including social and physical disorder, collective efficacy, residential mobility, and subcultural diversity). The final model, step 5 added measures of personal fear of crime (including fear of violent crime, fear of property crime, and fear of drug crime). The logist ic regression analysis (Table 4 18) revealed no statistically significant findings in step 1 (demographics), so when only accounting and controlling for variables like probationers race, age, and gender, there is not significant difference among participants. The Cox & Snell R 2 is .020 or 2%, however this is a pseudo R 2 and cannot be directly interpreted as the percent of the variance explained. To help us better determine the amount of variance explained by the a ddition of variables in each step, we also report the Negelkerke R 2 which adjusts the Cox & Snell R 2 so that the range extends to 1 (which the Cox & Snell lacks) (Negelkerke, 1991). We will discuss the Negelkerke R 2 for the subsequent findings. At step 1, the Negelkerke R 2 is .026 (or 2.6%) 26 Similarly, step 2 (offense history) and step 3 (current offense) had no 26 There are other type s of R square that would allow us to determine the proportional reduction in error, where the bigger the number the better the model fit, however those were not run as a part of the current

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113 current offense history was significant in predicting the use of defensive precautionary behaviors. The Negelkerke R 2 for step 2 is 6.3% ( or .063) and 7.8% in step 3 (or .078). So if the Negelkerke was interpreted as a traditional R 2 we could note that there is significantly more explained variance in model 2 (an increase of 3.7%) and model 3 (an increase of .052 from step 1 and 1.5% from step 2), with the addition of offense history and current offense. Step 4 added variables for perceptions of social disorganization. Here findings show no statistically sig and current offense. Interestingly, the addition of social disorganization variables resulted in only one variable being a significant predictor of defensive behaviors subcultural diversit y (with all other neighborhood variables having n o significance). Subcultural diversity was significant at the .05 alpha levels. So those who experience higher levels of perceived subcultural diversity are more inclined (or are more likely to) use defensiv e precauti onary behaviors to protect themselves (b coefficient of .473). With regard to the odds ratio, for every unit change in subcultural diversity, the percent change in the odds of using defensive behaviors are expected to change by a factor of 1.60 ( or 16%), on average, holding all other variables constant. The explained variance here is 13% (which is an increase of 5.2% from step 3). Finally, step 5 is the full model including demographics, offense history, current offense, and social disorganizat ion incorporates fear of crime variables to the analysis. analysis (other possible R 2 include the McFadden R 2 which treats the log likelihood of the model as the total sum of squares and the log likelihood of the whole model as the sum of squared errors (McFadden, 1973; McFadden, Puig, & Kirschner, 1977)

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114 Because the current analysis is theoretically driven, fear of crime variables were included into the analysis as the last step so that the effect of demographics, offense history, and social disor personal fear. Surprisingly, the only significant variable again was subcultural diversity (at the .05 alph a level). As shown in Table 4 18, it seems that probationers who experience higher per ceived subcultural diversity are more likely to use defensive behaviors (i.e. carry a gun, carry a weapon other than a gun, and/or buy and secure a gun) (b coefficient of .486). The percent change in the odds of using defensive behaviors is expected to cha nge by 16.3%, on average. Adding personal fear of crime to the model significantly increased the explained variance to 17.1% (from 13% so there was a 4% increase). Overall, only those participants who experienced or perceived higher levels of subcultural diversity in their neighborhood and communities were found to have a higher likelihood of using defensive behaviors (like buying a gun, carrying a gun, or carrying a weapon other than a gun) to protect themselves. Interestingly, demographics were not sign ificant predictors. This is not consistent with past research, which traditionally has found that gender, for example, plays a role in the type of precautionary behaviors we use. Specifically, the literature shows that males are more likely to use defensiv e behaviors like carrying a firearm than females (who are more likely to employ avoidance type behaviors or carry nonlethal defensive weapons) (Ferraro, 1995, Lane, 2009). It could be that participants are carrying weapons for reasons other than protectio n, like sport or recreation as Wright (1991) would argue (Ferraro, 1995). Wright notes that although we may believe individuals carry weapons as a form of protection it may be

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115 that the motivation is for reasons other than protection or self defense (Ferra ro, 1995; Wright, 1991). This could also be a limitation of the current studies sample size (n=202) and type of participant. One would assume that because this is an offending population, they would be more likely to participate in defensive behaviors as a mechanism of protection from possible victimization (because they are more involved in crime and therefore are more likely to be victims of crime). However, because they are on probation, they could have felt hesitant to indicate that they were carrying a weapon (as that would be a violation of probation) even though they were reassured that the survey was confidential. Maybe increasing the sample would make such differences among gender groups more evident. Although we anticipated more serious offender s to use defensive behaviors (rather than avoidance behaviors), it seems that our hypothesis is not supported. Offense history, offense seriousness, and current charge do not matter, based on the findings. Offending does not make a participant more likely to participate or use defensive precautionary behaviors. Because subcultural diversity was the only significant variable in predicting the likelihood of using defensive behaviors, it could be that perceiving people different from you in your community (or living in an ethically and racially diverse neighborhood) reduces ones likelihood to build community cohesion and thus results in distrust and fear among the community, which in turn result in offenders resorting to possessing a firearm to protect themselv es in their communities. Predicting avoidance precautionary b ehaviors Table 4 19 show the series of logistic regression estimated predict avoidance precautionary behaviors used by probationers. Here a theoretically driven step wise

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116 logistic regression an alysis shows the progressive addition of variables of interest in predicting the likelihood of using avoidance behaviors Step 1 includes demographics (race, age, sex), only sex was significantly associated with using avoidance precautionary behaviors (at t he .01 alpha level). B ased on the findings in Table 4 19, females were significantly more likely to use avoidance behaviors than males (b coefficient of .869). Because age and race were not found to be significant, it would suggest that there were no raci al or age differences among probationers in predicting their likelihood of using avoidance behaviors to protect themselves. The Negelkerke R 2 is, 047, meaning when only accounting for demographic factors, 4.7% of the variance is exampled. Step 2 adds offe nse history variables (violent, drug, property, public ordinance variables, and an offense seriousness scale). After accounting for offense history, sex continues to be a significant predictor (as in step 1). Again, females are more likely to indicate usin g avoidance behaviors than men. The only other significant predictor was having a violent offense history (at the .05 alpha level). So probationers who have more violent offenses in their criminal histories are less likely to participate in avoidance preca utionary behaviors (b coefficient of 1.02). Here, the addition of offense history increases the explained variance to 10.8 %, as denoted by the Negelkerke R 2 (.108). This is a significant increase of 6.1% in expla ined variance. Step 3 (Table 4 19) adds c urrent charges (property, drug, and public ordinance violent current charges were used as the reference). Here sex continues to remain significant (at the 05 alpha level), Again, as we see in step 1 and 2, females are more likely to use avoidance behavio rs than males (b coefficient of 1.01). Violent offense

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117 history is also significant at the .05 alpha level. Again, it seems that those probationers who have more violent offending in their offense history are less likely to use or employ any avoidance beha viors (b coefficient of 1.15). Using the Negelkerke R 2, the addition of current offense increases the explained variance to 11.8% (a 1% increase). Step 4 includes measures of perceived social disorganization (including social and physical disorder, colle ctive efficacy, residential mobility, and subcultural diversity). Again, sex is still a significant predictor of using avoidance behaviors. As indicated earlier, here we can see that females are more likely to report using avoidance behaviors than males. A dding neighborhood perceptions to the model resulted in offense history no longer being a significant predictor. Interestingly, neighborhood perceptions were not significant predictors of using avoidance behaviors as was anticipated. Yet, we see more varia nce explained by the addition of these variables (Negelkerke R 2 = .186 or 18.6%, which is a 6.8% increase). Step 5 accounts for personal fear of crime variables by adding measures of fear of violent crime, fear of property crime, and fear of drug crime to the model. After accounting for offense history, current history, neighborhood perceptions and personal fear of crime, sex continues to be a significant predictor for a voidance behaviors as shown in Table 4 19. So again we see females are more likely to indicate using avoidance precautionary behaviors than males, even after controlling for all other variables. No other variables were significant in the final model. Overall, gender and violent offense history were the only two variables found to be sign ificant predictors in the analysis. With regard to gender, throughout the series of logistic regressions (step 1 to 5) females were found to be more likely to report using

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118 avoidance precautionary behaviors. Meaning, females are more likely than males to in dicate they limit or change their daily routine, avoid certain areas of their neighborhood, and go out with someone so they are not alone. This is consistent with the previous literature, which has consistently noted females as being more likely to engage in avoidance behaviors than males (Ferraro, 1995; Lane, 2009; Lane & Meeker, 2004; Reid, Roberts, & Hilliard, 1998). While we anticipated offense history to have an effect on using precautionary behaviors, it seems that offense history played a small role in using avoidance behaviors. The only offense variable that was found to be significant was previous violent offending. However, we found that those who had more violent offenses in their criminal histories were less likely to use or indicate using avoida nce behaviors to cope with crime. One reason for this could be that these types of offenders are more likely to feel like they can protect themselves, so they chose not to avoid areas. It could also be argued that the more violent offenses committed would result in the use of defensive beha viors, but as we see in Table 4 18, when predicting defensive behaviors such results were not found. Also, we did not find any perceived social disorganization variables to be significant in predicting the use of avoidanc e behaviors. Theoretically, we would believe neighborhoods to play a role in the coping strategies probationers use to protect themselves. For example, Ferraro (1995) found that those who lived in neighborhoods that had incivilities were more likely to cha nge their daily routine. Perhaps more research is needed among offending populations to better understand the relationship between neighborhood perceptions, personal characteristics, offending and precautionary behaviors used.

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119 Predicting target h ardening precautionary b ehaviors Table 4 20 shows five step wise logistic regression models estimated to predict target hardening behaviors used by participants in the study. For each model, a series of variables are added to predict the likelihood of offenders u sing target hardening behaviors. In all five models, there were no statically significant variable found to predict the likelihood of engaging in target hardening beha viors (as indicated in Table 4 20). Model 1 (or step 1) shows demographic variables (a ge, race, sex). None of these demographic variables were found to be significant, so men are not more likely to participate or use target hardening behaviors to protect themselves than women (or vice versa). Similarly, there are no differences among differ ent racial groups or age groups among probationers in predicting their likelihood of using target hardening behaviors to protect themselves. The Negelkerke R 2 is .033, meaning when only taking into account probationers demographic characteristics, 3.3% of variance is explained. public ordinance history variables) and an offense seriousness scale. Even after adding ferences in the likelihood of engaging in target hardening behaviors. The addition of offending history increases the explained variance (as indicated by the Negelkerke R 2) to .037 (or 3.7%). Step 3 (Table 4 20) adds current offense to the step wise regr ession model. Property, drug, and public ordinance current offenses were used. Again violent current offense was used as the reference category. After controlling for demographics and offense history, there were no significant findings. So it could be tha t there is no difference in the likelihood of engaging in target hardening behaviors among

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120 probationers who committed different offenses that they are currently on probation for. With the addition of current offense variables, as shown in Table 4 20, the e xplained variance increased by 1.8% to 5.5% (Negelkerke R 2 = .055). Step 4 added measures of perceived social disorganization to the model. Interestingly, neighborhood perceptions (measured by social and physical disorder, collective efficacy, subcultur al diversity, and residential mobility) were not significant in predicting the likelihood of using target hardening behaviors. The Negelkerke R 2 was .081, meaning the model explains about 8.1% of the variance. Step 5 which included all variables (demog raphics, offense history, current offense, social disorganization) adds personal fear of crime to the final model. Again, here we see that personal fear of crime (including measures of fear of violent crime, drug crime, and property crime) was not a signif icant predictor of target hardening behaviors. The Negelkerke R 2 is .092. Controlling for such variables, the exaplained variance increased to 9.2%. Overall, here we can see that after accounting for several important variables like participant demograph ics, personal fear of crime, and neighborhood perceptions, we were unable to find any statistically significant predictors of the likelihood to use target hardening b ehaviors to protect themselves. Summary of Findings for Precautionary Behaviors It was o riginally hypothesized that a prior offense history would lead individuals to find methods to protect themselves and that offenders who had more serious criminal history would have engaged in defensive behaviors, rather than avoidance behaviors or target h ardening, to cope with crime. We also expected to find, based on past research by May (2001) and Lane (2009), that male probationers would be more likely to

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121 participate in defensive behaviors than female probationers who would have been more likely to rep ort using avoidance behaviors. However, hypotheses were partially supported. Logistic regression analysis predicting defensive behaviors showed no offense history seriousn ess made no difference. Although we thought more serious offenders would use defensive behaviors (because of their lifestyle and vulnerability to victimization), offense serious did not make a difference. Also, males were not found to be more likely than f emales to participate in defensive behaviors to protect themselves. When predicting avoidance behaviors however, gender did play a significant role in predicting the likelihood of using such precautionary behaviors. Table 4 19 revealed that females were more likely to report using avoidance behaviors than males (as was anticipated). Also, violent offending was significant here (unlike when predicting defensive behaviors) and those with more violent offenses in their criminal histories were less likely to use avoidance behaviors. While we would assume that those with more violent offenses would use defense behaviors to protect themselves because of the nature of the offenses they are committing, we did not find this when predictin g defensive behaviors (Tab le 4 18). Finally, personal fear of crime measures were not found to be significant predictors in either regression models. This is also not consistent with what we would expect. One would anticipate that being fearful of crime would lead to the use of avo idance or defensive precautionary behaviors as a way to cope with self from future victimization. Such findings could have resulted because the sample size in the present study (n=202) is so small. It could be that collecting mo re data on offending populations may help us better understand the

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122 role of offending, neighborhood perceptions, and fear of crime on the use of precautionary behaviors. Or it could be that those using precautionary behaviors are no longer afraid because th ey are protected. When predicting the use of targ et hardening behaviors (Table 4 20), there were no significant predictors for target hardening behaviors. So demographics, offense history, current offense, social disorganization, and personal fear of crim e were not able to predict the likelihood of using target hardening behaviors. This is interesting, and is unexpected. We would have expected most to engage in avoidance and/or target hardening behaviors (as Ferraro, 1995 notes). For example, Ferraro (1995 ) found that most participants either used avoidance behaviors or did things to protect their home (i.e. target hardening behaviors like adding locks to ones home and adding outside lighting). Few were noted to carry a gun or use defensive behaviors. It ma y be that having an sample of offenders plays a complex role in determining the types of precautionary behaviors offenders use to cope with crime and protect themselves from victimization. Qualitative Data Analysis Findings This section present the findin gs from qualitative analysis (we employed content analysis techniques) conducted on interview data collected on misdemeanant probationers. Content analysis is a method of examining and interpreting material that is qualitative in nature (meaning interviews and narratives given by participants which can be written and/or audio recordings) so that certain patterns, themes, and meanings can be found and interpreted (Berg, 2009, Berg & Latin, 2008; Leedy & Ormrod, 2005). There have been few studies to examine fear of crime from a qualitative perspective, and to date there has not been any qualitative work on fear of crime among

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123 offenders. It is the hope of this study that this qualitative section will build on the past works on fear of crime, specifically those among offending populations. In this section we will discuss in detail the themes and patterns f ound throughout the interviews. This section will address qualitative findings with regard to personal fear of crime, altruistic fear of crime, precautionary behaviors, and social disorganization. Personal Fear of Crime and Offending Qualitative f indings The qualitative component of the study allowed researchers to gain greater insight om the interviews conducted. When examining fear of crime and offending there were 18 different themes that were found throughout the transcripts (Table 4 21 ). Such themes may not have been captured by the quantitative data; however, qualitative data has p rovided us with the unique opportunity to better understand this relationship and Due to the semi structured nature of the interview process, researchers were able to ask participant s open ended follow up questions after asking more structured questions. One of the most notable themes present throughout the interviews were probationers indicating they were afraid of certain specific crimes (93.6%, n=189, Table 4 21 ). Most often partic ipants mentioned being afraid of a violent crime (56.9%, n= 115). Some offenders were general in the t ypes of crimes they feared. For example a 35 year would say I am afrai d of um just like the random violent activity, nothing specific

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124 Most however, were very specific in the types of crimes they listed being afraid of. Some who indicated being fearful also stated it was due to a recent experience of victimization A 34 year old black male on probation for not having a valid drivers license (public ordinance offense see Appendix I for a detailed breakdown of offenses and offense categories), for example, states: e been home invaded before so that why that's the fear that is kind of hard to get out of your mind so pretty much I go to sleep every night and I think about that If that happened to me again I don't know, I would be really scared. It makes me A nother participant (a 33 year old black male on probation for larceny an d petty theft (property crime) states: Um probably the getting robbed someone robbing me with a weapon. Because I can get killed, you know, over take my life over a couple bucks. Th have a better chance of killing you, man. Many participants also discussed the notion of whether or not participating in crime had a significant effect on their fear of crime. Few indicated that it had a significant effect on their fear; however, those that did often felt more afraid. Many stated that because they know what they are capable of, it makes them question what others can do to harm them. A 45 year old white female on probation for a DUI stated: Another participant had similar sentiments and stated (27 year old white male on probation for resistin g or obstructing an officer without violence (a public ordinance offense)):

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125 Scary Like you see what out there that other people don't, and aware and keep your eyes open. Interestingly, there were also some individuals who indicated that their participation in crime made them less afraid of crime because they are more aware of crime. A 36 year old white male on probation for battery (a violent offense) stated: Yes it does impact it, um, since, uh, I have indicated some of the my involvement in some crimes. I guess I would be more aware of what can happen at a given point time, and it would probably make me less afraid, um, just having that information and knowing what to do in those types of situations cause I can handle my self. Some indicated that their participation in crime had no effect on their fear levels. A participant who was on probation for domestic battery (a violent offense) (29 year old black male) stated: ook any better, ffect me either way. A participant on probation for DUI (25 year old white male) stated something Some distinguished between their offending affecting their fear versus their awareness of crime. A 27 year old white male on probation for aggravated battery with a weapon stated: Um neither. Neither more or less. Um. I mean raised awareness but I am not afraid of it.

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126 Similarly, a 22 year old white male who was on probation for possession of marijuana with the intent to s ell (a drug offense) stated: Well, I mean its made me more aware of it, I guess you could say it made more afraid But, if anything, it made me more understanding of it, you know, of the situation and the situation they are in. In summary, while we antici pated finding that participation in crime would increase probationers fear levels, it seems that it dose not have the effect that we had hypothesized. Qualitative interviews revealed that offending does not necessarily increase a probationer s fear of cri me. In fact, for some, it reduced their fear levels because they felt more aware of why and how crime operates. However, some probationers also indicated that their participation also made them more afraid because they know what people are capable of doin g and feel that their offenses puts them in a position to be victimized. These are interesting findings because we can see a variation in fear levels among offenders. Interestingly, many who indicated being more fearful said they were fearful of property c rimes most often or violent crimes that involved their property (like home invasions or robbery). These were also property and public ordinance offenders. Those who were on probation for violent offenses tended to indicate that they were less afraid of cri me or that their offending had not effect on their fear. Altruistic fear of crime and o ffending With regard to the qualitative information obtained on altruistic fear of crime (Table 4 22) many probationers mentioned the importance of protections or be ing fearful of certain crimes because of the presence of children or family. About 12% (n=25) of participants indicated being afraid for their family members. Of those who indicated fear for family, it was often focused on young children or older parents. A

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127 participant on probation for battery (23 year old black male) highlights this concern by discussing his fear of certain crimes when his young nieces and nephews are at home, showing that his fear specifically, is not for his own safety, but that younger children will be harmed. He states: s kind of, like, not a second chance to think. You know, like, should I but most --it would r eally be home invasion though or something where my kids or nieces and nephews are cause they can defend they self. Another participant on probation for assault (20 year old black female) compares her fear for her family compared to her own fear and state s: Um, my family is my pride, my joy, and I love them, I love them more than want to protect them from that Cause I mean you never know how this work is gonna end up and what is coming to you. Similar sentiments were expressed by a 48 year old black male who was on probation for trespassing (a property offense) He states: Um, my wife and then I have two smal ler children who I just feel if my whole life, I learned to fight early and can use anything for a weapon, or them than me cause I could pick up some dirt and make it a weapon but they defenseless. One participant also expressed these concerns, however, they were for family members that were older in age. A 45 year old white female on probation for DUI stated:

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128 About 34.2% (n=69) indicated that they were afraid for their family because of their participation in crime. One participant on probation for posse ssion and use of drug paraphernalia (a 32 year old black male) described how the type of crimes he participates in may put his family in danger. He stated: The drug sales, man, it can put people in danger, cause, I mean, like when you like living in drugs a lot of people think you got a lot of money or something like that. And, then they know where you live. They might just wanna come over and take whatever you have, like if you got some money or anything. It might not be nothing else just because you got a homeboy situation can put my fam. in jeopardy, you know. That real and that scary. Qualitative data (Table 4 22) revealed that participants had family who were victims of crime. Moreo ver, 24.3% of the sample indicated they were afraid for a family member. Similar to what we found in the descriptive resu lts for altruistic fear (Table4 10 and Table 4 11) most probationers were afraid for a close family member (like their mother or fathe r or son or daughter). We also found that while some indicated being fearful for family because of their participation in crime, interviews show that some offenders fear levels were unaffected or reduced due to their participation in crime. Precautionary Behaviors and Offending Qualitative f indings There were several interesting themes that were present in the interviews concerning precautionary behaviors as shown in Table 4 23 Most notable were use of precautionary beh aviors and how diverse participants were in the types of behaviors they engaged in. Many spoke about engaging in target hardening behaviors like a participant who was on probation for worthless checks (50 year old black female) who stated:

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129 I installed ex tra locks in the home to keep them [criminals] from getting in, age. Bought a watchdog. I like dogs, d A 46 year old white female on probation for violation of a domestic injunction (public ordinance offense) discussed participating in similar efforts to protect herself (target hardening). and then usually people run away, so my only reason for getting him was that reason. Some participants shared about their defensive efforts in protecting themselves from victimization. A 31 year old black male on probation for domestic battery stated: Um like with buying a gun, just in case something doe s happen, when someone breaks in my house I wanna be able to protect my self. I got a bat too, but the gun, I know I am protected from all the violent crimes out there. While many probationers indicated the use of avoidance behaviors (as was found in the behaviors. A 24 year old white female (on probation for) discussed the use of different methods to protect her self: I carry a weapon, pepper spray and sometimes a knife. But I also arrange to go out with other people so I am not by myself. That way I don't feel afraid like I need to use a weapon, but if I have to, and I have, I will. A 23 year old black male on probation for DUI also discussed using multiple approaches to prote cting himself from victimization: I carry a knife and arrange to go out with someone so you wouldn't be alone on. But I always be prepared, like I avoid those areas like that part o f the

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130 Based on the qualitative interviews conducted, we can see that probationers employ several techniques to protect themselves from crime. Although descriptive statistics show that few offenders indicated usi ng p recautionary behaviors (Table 4 13), qualitative findings show something different. From the interviews, as shown above, we found that many (about 82% Table 4 23 ) mentioned trying to protect themselves from some type of crime. Probationers mentioned participating in avoidance behaviors, defensive and target hardening behaviors. Interestingly, as stated above, some probationers mentioned that they participated in several types of behaviors. For example, having a gun (defensive) and buying locks and lig hts for their homes (target hardening). Finally, we also found that many felt that participating and engaging in such precautionary behaviors helped keep them safe from being victimized. So while quantitatively we were unable to determine the role that pre cautionary behaviors play in from being victimized (even though they participate in crime themselves). Fear of crime and social d isorganization T able 4 24 highlights the themes found present throughout the interviews with to researchers because probationers carry their sentence out in the community, which could possibly affect the ir fear levels. This was also an important component because of the effect that perceived disorder and subcultural diversity may have on fear of crime. Much of the literature has pointed out the importance of neighborhood disorder, collective efficacy, an d subcultural diversity on fear of crime (Lane, 2002). In fact, many

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131 communities cri tical. When asked to describe their neighborhood, some participants described their neighborhood to be living in an area that was low income and that many lived in poverty. Others described living in an area where there are many college students or an are a that was middle class. A 26 year old female on probation for possession of drug paraphernalia talked about the individuals living in her community and elaborated on the difficulties of employment and income. She stated: here are a lot of survive I think they have a lot of assis Another participant (23 year old black male on probation for possession of marijuana) stated somethi ng similar when asked to describe his neighborhood in in terms of poverty: uh I would say pretty much everybody a new ride or a nice crib we be trying to make it every day, but it be hard to make money in the economy you k Many probationers also mentioned being able to rely on their neighbors for help (n=136, 67%), there were, however, some participants who indicated not being able to rely on their neighbors for help (n=52, 26%). This is an important indicator of percei ved neighbors and what they could rely on them for, one participant (26 year old black male ll no, nothing,

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132 Similarly, a 29 year old male on probation for domestic battery stated: but h anything or watch out for me. not rely on them for anything. Here we can see that the pa perceptions of his community. Some probationers indicated having a difficulty trusting neighbors because of their inability to communicate with one another. A 34 year old w hite male on probation for DUI indicated population living in his community (an indicator of subcultural diversity). He states: most peop even talk to them. When probationers were asked to describe the physical and social condition of their neig hborhood, many indicated kids drinking on the street, drugs, vandalism or garbage to be the biggest issue in their neighborhood. Most also stated that gangs and violent crimes were the least problematic in their communities. So it seems that most individua ls on probation do not perceive serious (or violent) crimes to problematic in their communities. Most noted drug and property related offenses to be the most problematic for them. For example, a 43 year old black male on probation for DUI states: You know all the kids here be going and doing drugs and drinking at night and then go around and tag up cars and houses, and vandalism is also a anything. I think one time there was ki ds fighting over some drugs or something and they ended up going to jail but not a lot of that.

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133 Another participant states (31 year old white male on probation for DUI): Uh, most problematic is vandalizing and drunk people trying to break into other peopl car and least problematic? I would say murder is not a problem in our, in our neighborhood. Overall, although we were unable to find much through our quantitative findings on neighborhood perceptions, qualitative data (as shown in Table 4 24) has helped shed some light on their communities. Because this is a sample of individuals on probation, it was interesting to find that many described living in communities where they coul d trust their neighbors and rely on them for some things. We also found that of those who indicated having some type of physical or social disorder present in their communities, it was usually vandalism, drugs, or kids drinking. Very few indicated more vio lent crimes being an issue. Finally, when asked if such things had any impact on their fear, many did not indicate that their neighborhoods or that the level of crime in their communities had an impact on their fear levels.

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134 Table 4 1. Interviewed Sample: Sample Characteristics (original & convenience sample) 27 Full Sample (n=202) Original Sample (n=153) Convenience Sample (n=49) % N % N % N Sex Male 63.4% 128 63.4% 97 63.3% 31 Female 36.6% 74 36.6% 56 36.7% 18 Race White 59.9% 12 1 59.5% 91 61.2% 30 Black 39.6% 80 39.9% 61 38.8% 19 Asian 0.5% 1 0.7% 1 ___ ___ Ethnicity Hispanic 6.4% 13 6.5% 10 6.1% 3 Non Hispanic 93.1% 188 93.5% 143 93.9% 46 Age 19 22 12.4% 25 8.5% 13 24.4% 12 23 27 20.4% 41 23.6% 36 10.1% 5 28 32 16.0% 32 13.8% 21 22.4% 11 33 37 11.0% 22 9.8% 15 14.3% 7 38 42 8.5% 17 7.3% 11 12.2% 6 43 47 11.5% 23 12.6% 19 8.1% 4 48 52 10.0% 20 11.8% 18 4.0% 2 53 57 4.0% 8 5.3% 8 ___ ___ 58 62 6.0% 12 7.3% 11 2.0% 1 63 69 1.0% 2 0.7% 1 2.0% 1 Educational Background 4 th 5 th Grade 0.5% 1 0.7% 1 ___ ___ 6 th 8 th Grade 2.0% 4 2.7% 4 ___ ___ 9 th 11 th Grade 9.4% 19 8.5% 13 12.2% 6 12 th Grade/HS Graduate 31.7% 64 33 .3% 51 26.5% 13 GED 7.4% 15 7.2% 11 8.2% 4 Some College 31.2% 63 28.1% 43 40.8% 20 AA/AS 5.4% 11 6.5% 10 2.0% 1 PhD 0.5% 1 0.7% 1 ___ ___ LPN 1.0% 2 1.3% 2 ___ ___ Vocational 1.0% 2 1.3% 2 ___ ___ Missing Response 1.5% 3 1.3% 2 2.0% 1 Employment History Full Time 38.1% 77 38.6% 59 36.7% 18 Part Time 18.3% 37 17.0% 26 22.4% 11 Self Employed 1.5% 3 1.3% 2 2.0% 1 27 Independent sample t test and chi square were run to determine if the re were any significant differences among those in the original sample, where participants were part of a random sample, and those in the convenience sample. There were no significant differences found between the two groups for most variables. Only plea bargaining and employment status were found to be different between the two groups at the .001 and .05 level (respectively).

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135 Table 4 1 Continued Full Sample (n=202) Original Sample (n=153) Convenience Sample (n=49) % N % % N % Not Employed 28.7% 58 28.8% 44 28.6% 4 Disabled 5.9% 12 7.8% 12 ___ ___ Student 5.4% 11 5.2% 8 6.1% 3 Retired 0.5% 1 0.7% 1 ___ ___ Homemaker 0.5% 1 0.7% 1 ___ ___ Missing Response 0.5% 1 ___ ___ 4.0% 2 Marital Status Married 13.4% 27 13.1% 20 14.3% 7 Divorced 19.8% 40 19.6% 30 20.4% 10 Separated 6.4% 13 7.2% 11 4.1% 2 Never Married 51.0% 103 50.3% 77 53.1% 26 Living with partner 8.4% 17 9.2% 14 6.1% 3 Missing Response 1.0% 2 0.7% 1 2.0% 1 Have Children Yes 60.4% 122 61.4% 94 57.1% 28 No 39.6% 80 38.6% 59 42.9% 21

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136 Table 4 2. Interviewed Sample: Current Offense Characteristics (original & convenience sample) Full Sample (n=202) Original Sample (n=153) Convenience Sample (n=49) % N % N % N Current Offense (Official): Violent/Persons Offenses 21.8% 44 25.5% 39 10.2% 5 Property Offenses 10.4% 21 7.2%% 11 20.4% 10 Drug Offenses 7.4% 15 7.2%% 11 8.2%% 4 Public Ordinances 60.4% 122 60.1% 92 61.2% 30 Number of Charges One 78.7% 159 78.4% 120 79.6% 39 Two 15.8% 32 15.7% 24 16.3% 8 Three 3.9% 8 3.9% 6 4.1% 2 Four 0.5% 1 0.7% 1 ____ ____ Six 1% 2 1.3% 2 ____ ____ Length of Probation Sentence (Official): 6 Months 14.9% 30 9.2% 14 32.7% 16 9 Months 1.0% 2 0.7% 1 2.0% 1 12 Months 84.2% 170 90.2% 138 65.3% 32 Length of Probation Sentence (Self Report): 3 Months 0.5% 1 0.7% 1 _____ _____ 4 Months 1.0% 2 _____ _____ 4.1% 2 6 Months 21.8% 44 19.6% 30 28.6% 14 7 Months 0.5% 1 __ ___ _____ 2.0% 1 10 Months 0.5% 1 0.7% 1 _____ _____ 11 Months 0.5% 1 _____ _____ 2.0% 1 12 Months 69.3% 140 72.5% 111 59.2% 29 18 Months 2.5% 5 2.6% 4 2.0% 1 24 Months 2.5% 5 2.6% 4 2.0% 1 36 Months 0.5% 1 0.7% 1 _____ _____ Missing Respons es 0.5% 1 0.7% 1 _____ _____ Length Served (At Interview): Less than a month 1.5% 3 _____ _____ 6.1% 3 1 to 3.5 Months 30.2% 61 27.6% 42 38.7% 19 4 to 6 Months 43.1% 87 47.2% 72 30.5% 15 7 to 9 Months 17.4% 35 16.9% 26 18.3 % 9 10 to 18 Months 8.0% 16 8.5% 13 6.1% 3 Plea Bargained: Yes 74.3% 150 74.5% 114 73.5% 36 No 21.3% 43 19.6% 30 26.5% 13 Missing Responses 4.5% 9 6.0% 9 _____ _____

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137 Table 4 3. Interviewed Sample: Official Prior Criminal History (original & convenience sample) Full Sample (n=202) Original Sample (n=153) Convenience Sample (n=49) % N % N % N Violent/Persons Offenses: Present 30.7% 62 31.4% 48 28.6% 14 Not Present 40.6% 82 39.2% 60 44.9% 22 No Previous Adult History 28.7% 58 29.4% 45 26.5% 13 Property Offenses: Present 42.1% 85 40.5% 62 46.9% 23 Not Present 29.2% 59 30.1% 46 26.5% 13 Not Previous Adult History 28.7% 58 29.4% 45 26.5% 13 Drug Offenses: Present 34 .7% 70 37.3% 57 26.5% 13 Not Present 36.6% 74 33.3% 51 46.9% 23 Not Previous Adult History 28.7% 58 29.4% 45 26.5% 13 Public Ordinance Offenses: Present 58.4% 118 60.1% 92 53.1% 26 Not Present 12.9% 26 10 .5% 16 20.4% 10 Not Previous Adult History 28.7% 58 29.4% 45 26.5% 13 Juvenile Record: Yes 8.9% 18 9.2% 14 8.2% 4 No 91.1% 184 90.8% 139 91.8% 45 Presence of Prior Adult CH: Yes 7 1.3% 144 70.6% 108 73.5% 36 No 28.7% 58 29.4% 45 26.5% 13 Table 4 4. Official Criminal History Measures Descriptive Statistics Minimum Maximum Mean SD Seriousness Scale 1 15 3.56 3.90 Diversity Measure 1 3 1.50 .916 Type Dummy Drug Offendi ng 0 1 .486 .502 Property Offending 0 1 .590 .494 Violent Offending 0 1 .431 .497 Public Ordinance 0 1 .819 .386

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1 38 Table 4 5. Interviewed Sample: Self Report Criminal History (original & convenience sample) Full Sample (n=202) Original Sample (n= 153) Convenience Sample (n=49) % N % N % N Self Report Criminal History: Rape/Sexual Assault 1% 2 0.7% 1 2% 1 Attack someone weapon 9.9% 20 11.1% 17 6.1% 3 Steel Car 5.9% 12 7.2% 11 2% 1 Robbing someone 4% 8 3.3% 5 6.1% 3 Vandalize property 24.3% 49 23.5% 36 26.5% 13 Threaten no weapon 13.9% 28 13.1% 20 16.3% 8 Assault no weapon 37.1% 75 37.3% 57 36.7% 18 Shot at someone while walking 3.5% 7 3.9% 6 2% 1 Damage property with graffiti 11.4% 23 10.5% 16 14.3% 7 Breaking in to someone home 10.4% 21 11.8% 18 6.1% 3 Home Invasion 1.5% 3 0.7% 1 4.1% 2 Drive by shooting 2% 4 2% 3 2% 1 Harass someone 30.7% 62 28.8% 44 36.7% 18 Carjacking 1% 2 1.3% 2 Dealt Drugs 24.8% 50 24.8% 38 24.5% 12 Possess Drugs 48% 97 47.7% 73 49% 24 Stol e money/prop with force 6.9% 14 6.5% 10 8.2% 4 Stole money/prop no force 17.8% 36 15.7% 24 24.5% 12 Table 4 6. Social Disorganization Descriptive Statistics Minimum Maximum Mean SD Social Disorder 1 4 1.53 .598 Physical Disorder 1 4 1.39 .550 Col lective Efficacy 0 1 0.813 .293 Subcultural Diversity 1 3 2.11 .765 Residential Mobility 1 3 1.82 .841 Table 4 7. Fear of Crime Descriptive Statistics Minimum Maximum Mean SD Fear of Violent Crime 1 4 2.41 1.03 Fear of Property Crime 1 4 2.15 .794 Fear of Drug Crime 1 4 2.11 1.21 General Fear of Crime 1 4 2.32 .907

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139 Table 4 8. Fear of Crime Descriptive Statistics (for each item) Minimum Maximum Mean SD Fear of Violent Crime: Being murdered 1 4 2.88 1.349 Being attacked with a we apon 1 4 2.70 1.219 Being robbed or mugged 1 4 2.50 1.227 Being beaten up 1 4 2.03 1.106 Being shot at while walking 1 4 2.57 1.318 Being the victim of a drive by 1 4 2.52 1,372 Being attacked without a weapon 1 4 2.06 1.149 Being the victim of a ca rjacking 1 4 2.16 1.186 Having money/property taken with force 1 4 2.47 1.206 Home invasion robbery 1 4 2.60 1.239 Fear of Property Crime: Having your car stolen 1 4 2.07 1.219 Having your property damaged 1 4 2.05 0.981 Having property da maged by graffiti 1 4 1.70 1.009 Having someone break in while away 1 4 2.36 1.129 Having someone break in while there 1 4 2.54 1.222 Having money/Property taken no force 1 4 1.90 1.056 Fear of Drug Crime 1 4 2.11 1.210 Table 4 9. Fear of Crime Frequencies (for each item) N=202 Not Afraid Somewhat Afraid Afraid Very Afraid N % N % N % N % Fear of Violent Crime: Being murdered 57 28.2 20 9.9 13 6.4 112 55.4 Being attacked with a weapon 48 23.3 43 21.3 32 15.8 79 39.1 Bei ng robbed or mugged 61 30.2 44 21.8 32 15.8 65 32.2 Being beaten up 90 44.6 46 22.8 36 17.8 30 14.9 Being shot at while walking 78 38.6 20 9.9 15 7.4 89 44.1 Being the victim of a drive by 76 37.6 24 11.9 20 9.9 82 40.6 Being attacked without a weapon 83 41.1 46 22.8 38 18.8 35 17.3 Being the victim of a carjacking 84 41.6 38 18.8 39 19.3 41 20.3 Having money/property taken with force 63 31.2 40 19.8 41 20.3 58 28.7 Home invasion robbery 59 29.2 34 16.8 38 18.8 71 35.1 Fear of Property C rime: Having your car stolen 81 40.1 48 23.8 44 21.8 29 14.4 Having your property damaged 53 26.2 73 36.1 58 28.7 18 8.9 Having property damaged by graffiti 115 56.9 46 22.8 21 10.4 20 9.9 Having someone break in while away 59 29.2 58 28.7 39 19.3 46 22.8 Having someone break in while there Having money/Property taken no force 99 49 48 23.8 31 15.3 24 11.9 Fear of Drug Crime 95 47 31 15.3 34 16.8 42 20.8

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140 Table 4 10. Altruistic Fear of Crime Descriptive Statistics N Minimum Maximum Mean SD Fear for family compared to self 202 1 3 2.31 .758 Fear by type of family member: Fear for Father 54 1 4 1.78 1.08 Fear for Mother 79 1 4 2.05 1.24 Fear for Husband 22 1 4 1.59 1.09 Fear for Wife 27 1 4 1.85 1.13 Fear for Son 70 1 4 2.43 1.23 Fear for Daughter 61 1 4 2.62 1.27 Table 4 11. Altruistic Fear of Crime Frequencies Lives with family member Not Afraid Afraid Min Max Mean SD N % N % N % Fear for family compared to self 202 100 Fear by type of family member: Fear for Father 54 26.7 32 59.3 22 40.7 0 1 .407 .496 Fear for Mother 79 39.1 40 50.6 39 49.4 0 1 .494 .503 Fear for Husband 22 10.9 16 72.7 6 27.3 0 1 .273 .456 Fear for Wife 27 13.4 15 55.6 12 44.4 0 1 .444 .506 F ear for Son 70 34.7 48 68.6 22 31.4 0 1 .686 .468 Fear for Daughter 61 30.2 17 27.9 44 72.1 0 1 .721 .452 *N = represents the number o individuals who indicated living with that family member, Not Afraid = the number of individuals who indicated not bei ng afraid for those family members out of the whole 202 participants, Afraid= the number of individuals who indicated being afraid for those family members. The percent for those who indicate afraid and not afraid is out of those who indicated they will wi th that particular family member and the percent (N) column indicates the percent of individuals who indicated living with each listed family member out of the 202 participants. Table 4 12. Precautionary Behaviors Descriptive Statistics Minimum Maximu m Mean SD Defensive Behaviors 0 1 .231 .309 Avoidance Behaviors 0 1 .457 .348 Target Hardening Behaviors 0 1 .293 .321

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141 Table 4 13. Precautionary Behaviors Descriptive Statistics (for each item) N=202 Yes* % No* % Min Max Mean SD Defensive Behavi ors: Buy or secure a gun 38 18.8 164 81.2 0 1 .19 .392 Carry a gun 29 14.4 173 85.6 0 1 .14 .352 Carry a weapon other than a gun 73 36.1 129 63.9 0 1 .35 .479 Avoidance Behaviors: Limit or change your daily routine 55 27.2 147 72.8 0 1 .27 .446 Avoid certain areas of your neighborhood 124 61.4 78 38.6 0 1 .61 .488 Go out with someone so not alone 98 48.5 104 51.5 0 1 .49 .501 Target Hardening Behaviors: Buy an alarm o security system 51 25.2 151 74.8 0 1 .24 .427 Install extra locks on your home or car 62 30.7 140 69.3 0 1 .30 .460 Buy a watchdog 44 21.8 158 78.2 0 1 .21 .419 Add outside lighting 80 39.6 122 60.4 0 1 .39 .489 *Yes = the number of participants who indicated that they engage in eac h of the listed precautionary behaviors, No = the number of participants who indicated that they do not engage in each of the listed participants.

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142 Table 4 14 OLS Regression Predicting General Fear of Crime Step 1: Control Variables Step 2: Offens e History Step 3: Current Offense Step 4: Social Disorganization B SE B SE B SE B SE Age .007 .005 .099 .007 .005 .093 .009 .005 .117 .008 .005 .111 White .351** .124 .190 .404** .137 .219 .268 .149 .145 .273 .154 .148 Male .507*** .126 .270 .539*** .131 .287 .551*** .131 .293 .576*** .136 .307 Offense History Violent .025 .174 .013 .044 .176 .022 .043 .180 .022 Drug .181 .181 .095 .156 .182 .082 .181 .185 .095 Property .055 .1 48 .030 .032 .146 .017 .025 .147 .013 Ordinance .301 .168 .164 .259 .168 .141 .209 .171 .114 Seriousness Scale .018 .029 .078 .025 .030 .108 .023 .030 .101 Current Offense Drug .200 .249 .058 .147 .25 2 .043 Property .680** .216 .225 .669** .218 .221 Ordinance .338* .141 .183 .325* .143 .175 Social Disorder .079 .151 .052 Physical Disorder .044 .154 .027 Collective Efficacy .437* .228 .141 Residential Mobility .031 .084 .029 Subcultural Diversity .002 .087 .001 Constant 2.585*** .229 2.634*** .238 2.378*** .255 1.903*** .410 F statistic 8.851*** 3.858*** 3.840*** 2.891*** R 2 .118 .138 182 .200

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143 Table 4 15 OLS Regression Predicting Fear of Violent Crime Step 1: Control Variables Step 2: Offense History Step 3: Current Offense Step 4: Social Disorganization B SE B SE B SE B SE Age .007 .006 .085 .007 .006 .079 .009 .006 .103 .008 .006 .096 White .417** .142 .199 .475** .157 .227 .319 .170 .152 .328 .176 .156 Male .515*** .144 .241 .556*** .150 .260 .573*** .150 .268 .602*** .155 .282 Offense History Violent .005 .19 9 .002 .077 .201 .035 .068 .206 .031 Drug .203 .207 .094 .166 .208 .077 .194 .212 .090 Property .094 .169 .045 .068 .166 .033 .064 .169 .031 Ordinance .369 .192 .177 .314 .192 .150 .257 .196 .123 Seriousness Scale .024 .033 .089 .031 .034 .116 .029 .035 .112 Current Offense Drug .180 .284 .046 .120 .288 .031 Property .771** .247 .224 .750** .250 .218 Ordinance .391 .161 .186 .377 .163 .179 Social Disord er .048 .173 .028 Physical Disorder .080 .176 .043 Collective Efficacy .478 .262 .136 Residential Mobility .018 .096 .015 Subcultural Diversity .004 0.99 .003 Constant 2.727*** .262 2.783* ** .273 2.492*** .292 1.970*** .476 F statistic 7.659*** 3.494*** 3.562*** 2.667*** R 2 .104 .126 .171 .187

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144 Table 4 16 OLS Regression Predicting Fear of Property Crime Step 1: Control Variables Step 2: Offense History Step 3: Cur rent Offense Step 4: Social Disorganization B SE B SE B SE B SE Age .008 .004 .116 .007 .005 .114 .009 .005 .133 .009 .005 .130 White .231* .108 .143 .273* .121 .169 .173 .131 .107 .171 .135 .106 Male .493*** .110 .300 .507*** .115 .309 .511*** .116 .311 .529*** .120 .322 Offense History Violent .080 .153 .047 .017 .155 .010 .003 .158 .002 Drug .141 .159 .085 .137 .161 .082 .157 .163 .094 Property .015 .130 .009 .036 .128 .022 .048 .130 .030 Ordinance .175 .147 .109 .15 8 .148 .098 .120 .151 .074 Seriousness Scale .008 .026 .041 .015 .026 .072 .012 .027 .059 Current Offense Drug .237 .219 .078 .198 .222 .065 Property .514** .190 .194 .521** .192 .196 Ordinance .242 .124 .149 .230 .126 .142 Social Disorder .138 .133 .104 Physical Disorder .023 .136 .016 Collective Efficacy .362 .201 .134 Residential Mobility .053 .074 .057 Subcultural Diversity .012 .076 .011 Constant 2.326*** .200 2.360*** .209 2.171*** .226 1.658*** .364 F statistic 9.361*** 3.788*** 3.518*** 2.709*** R 2 .124 .136 .169 .190

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145 Table 4 17 OLS Regression Predicting Fear of Drug Crime Step 1: Control Variables Step 2: Offense History Step 3: Current Offense Step 4: Social Disorganization B SE B SE B SE B SE Age .020** .007 .199 .016* .007 .162 .017* .007 .173 .016* .007 .157 White .376* .164 .152 .318 .180 .129 .191 197 .078 .125 .202 .051 Male .616*** .167 .246 .733*** .171 .292 .751*** .174 .300 .746*** .179 .298 Offense History Violent .215 .227 .082 .259 .233 .099 .324 .237 .124 Drug .186 .236 .073 .244 .241 .0 96 .271 .244 .107 Property .131 .193 .053 .103 .193 .042 .053 .194 .022 Ordinance .664** .219 .271 .664** .223 .271 .611** .225 .249 Seriousness Scale .029 .038 .095 .029 .039 .093 .035 .040 .112 Current Offense Drug .565 .330 .123 .546 .332 .119 Property .387 .286 .096 .378 .288 .094 Ordinance .272 .185 .110 .236 .187 .095 Social Disorder .364 .199 .180 Physical Disorder .022 .202 .010 Colle ctive Efficacy .577 .301 .140 Residential Mobility .078 .110 .054 Subcultural Diversity .033 .114 .021 Constant 2.013*** .304 1.957*** .312 1.738*** .339 1.005*** .547 F statistic 9.655*** 5.074*** 4.081*** 3.276*** R 2 .128 .174 .191 .221

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146 Table 4 18 Logistic Regression Predicting Use of Defensive Precautionary Behaviors Step 1: Control Variables Step 2: Offense History Step 3: Current Offense Step 4: Social Disorganizati on Step 5: Fear of Crime B SE OR B SE OR B SE OR B SE OR B SE OR Age .023 .012 .978 .017 .013 .983 .015 .013 .985 .015 .014 .985 .010 .014 .990 White .121 .294 1.13 .165 .331 1.18 .368 .370 1.45 .365 .391 1.44 .262 .402 1.29 Male .101 .297 .904 .076 .314 .059 .109 .322 .897 .084 .341 1.08 .249 .373 .780 Offense History Violent .357 .424 .700 .309 .439 .496 .374 .460 .688 .291 .471 .747 Drug .179 .439 1.19 .096 .452 1.10 .108 .465 1.11 .010 .4 76 1.01 Property .565 .361 .568 .530 .362 .588 .621 .377 .537 .665 .386 .514 Ordinance .520 .406 .594 .541 .418 .582 .559 .436 .572 .370 .450 .691 Seriousness Scale .109 .072 1.12 .114 .075 1.12 .134 .077 1.14 .122 .077 1.13 Current Offense Drug .579 .644 1.78 .884 .641 2.42 1.07 .651 2.94 Property .303 .582 1.35 .538 .546 1.71 .814 .578 2.25 Ordinance .234 .413 .791 .075 .431 .928 .137 .444 .872 Social Disorder .227 .379 1.25 .354 .391 1.42 Physical Disorder .490 .389 .613 .508 .392 .602 Collective Efficacy .038 .208 .963 .333 .577 .717 Residential Mobility .473 .219 1.60 .486 .223 1.63 Subcultu ral Diversity Fear of Violent Crime .123 .266 .884 Fear of Property Crime .133 .346 .876 Fear of Drug Crime .243 .178 .784 Constant .583 .545 1.79 .517 .572 1.68 .42 2 .635 1.53 .192 1.02 1.21 .655 1.12 1.93 X 2 4.01 5.78 2.42 8.37 6.95 Cox & Snell R 2 .020 .047 .059 .097 .127 Negelkerke R 2 .026 .063 .078 .130 .171 2 log likelihood 273.6 270.2 267.8 257.1 250.1

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147 Table 4 19 Logistic Regression Predicting Use of Avoidance Precautionary Behaviors Step 1: Control Variables Step 2: Offense History Step 3: Current Offense Step 4: Social Disorganization Step 5: Fear of Crime B SE OR B SE OR B SE OR B SE OR B SE OR Age .012 .013 .988 .008 .015 .002 .0.08 .015 .992 .002 .015 .998 .001 .016 .999 White .055 .335 .946 .274 .388 .760 .290 .429 .749 .110 .444 .895 .105 .450 .900 Male .869** .370 .419 .954** .391 .385 1.01* .402 .362 1.03* .417 .356 1.02* .439 .362 Offense History Violent 1.02* .464 .362 1.15* .481 .316 .952 .499 .386 .919 .502 .399 Drug .437 .501 1.55 .442 .514 1.56 .210 .533 1.23 .309 .496 1.36 Property .140 .407 1.15 .114 .410 1.12 .197 .430 1.22 .452 .795 .637 Ordinance .150 .459 1.16 .115 .466 1.12 .238 .487 1.27 .309 .496 1.13 Seriousness Scale .037 .078 .964 .017 .081 .983 .017 .085 .983 .020 .085 .980 Current Offense Drug .448 .737 .639 .435 .794 .647 .452 .795 .637 Property .765 .656 .465 .521 .693 .594 .581 .707 .559 Ordinance .249 .468 .780 .186 .499 .831 .223 .506 .800 Social Disorder .628 .504 1.87 .592 .50 3 1.81 Physical Disorder .571 .522 1.77 .625 .527 1.86 Collective Efficacy .193 .748 .825 .187 .755 .830 Residential Mobility .230 .257 1.25 .223 .257 1.25 Subcultural Diversity .0866 .258 .917 .096 .260 .908 Fear of Violent Crime .085 .308 .918 Fear of Property Crime .323 .395 1.38 Fear of Drug Crime .159 .211 .853 Constant 2.12 .65*** 8.35 2.35 .69*** 10.4 2.69 .78*** 14.6 .505 1.36 1 .66 .325 1.47 1.38 X 2 6.63 8.86 1.43 5.36 9.84 Cox & Snell R 2 .032 .074 .080 .127 .131 Negelkerke R 2 .047 .108 .118 .186 .192 2 log likelihood 223.7 214.9 213.5 203.1 202.1

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148 Table 4 20 Logistic Regres sion Pr edicting Use of Target Hardening Precautionary Behaviors Step 1: Control Variables Step 2: Offense History Step 3: Current Offense Step 4: Social Disorganization Step 5: Fear of Crime B SE OR B SE OR B SE OR B SE OR B SE OR Age .009 .012 1.01 .0 10 .013 1.01 .011 .013 1.01 .012 .013 1.01 .012 .014 1.01 White .424 .297 .654 .479 .327 .619 .495 .368 .610 .378 .383 .685 .345 .388 .708 Male .453 .303 .636 .430 .314 .650 .365 .322 .694 .279 .334 .757 .257 .357 .773 Offen se History Violent .103 .351 .902 .092 .433 .912 .056 .445 .945 .100 .450 .905 Drug .073 .374 .930 .252 .446 .777 .353 .462 .703 .328 .466 .721 Property .036 .327 1.04 .021 .354 .979 .036 .362 .964 .002 .368 1.00 Or dinance .042 .388 .959 .006 .409 .994 .074 .422 1.08 .013 .434 1.01 Seriousness Scale .044 .070 1.05 .020 .073 1.02 .010 .075 1.01 .016 .076 1.02 Current Offense Drug .781 .651 2.18 .869 .678 2.38 .946 .691 2.57 Property .877 .609 2.40 .840 .627 2.32 .824 .633 2.28 Ordinance .444 .631 1.56 .487 .423 1.63 .553 .429 1.74 Social Disorder .076 .377 .927 .056 .386 .945 Physical Disorder .438 .400 1.55 .416 .407 1.52 Collective Efficacy .588 .577 .556 .632 .585 .532 Residential Mobility .268 .209 .765 .256 .211 .774 Subcultural Diversity .191 .216 1.21 .190 .217 1.21 Fear of Violent C rime .309 .262 1.36 Fear of Property Crime .372 .341 .689 Fear of Drug Crime .046 .174 1.05 Constant .488 .548 1.63 .484 .571 1.62 .054 .631 1.06 .031 1.07 .969 .125 1.14 .882 X 2 4.984 .617 3. 318 4.11 1.77 Cox & Snell R 2 .024 .027 .041 .061 .069 Negelkerke R 2 .033 .037 .055 .081 .092 2 log likelihood 271.2 270.5 267.6 263.5 261.7

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149 Table 4 21 Fear and Offending Themes (types of crimes) % (Yes) N (N=202) 1. Does the participant mention being afraid of any crimes? 93.6% 189 a. Do they mention a specific crime? 92.1% 186 b. Do they mention multiple crimes? 40.6% 82 c. Does the participant mention violent crimes? 56.9% 115 d. Do they mentio n property crimes? 17.3% 35 e. Do they mention drug crimes? 17.8% 36 2. Does the participant mention not being afraid crime? 91.6% 185 3. Does the participant mention crimes they are least afraid of? 85.1% 172 a. Is there a mention of a specific crime? 22.3% 4 5 b. Do they mention multiple crimes they are not afraid of? 32.7% 66 c. Does the participant mention not being afraid of violent crimes? 27.7% 56 d. Does they participant mention being least afraid of property crimes? 6.4% 13 e. Do they mention being least afra id of drug offenses? 47.5% 96 4. Is there a mention of them being a victim of a previous crime? 47% 95 a. Do they mention what type of crime it was? 46.5% 94 5. Does the participant mention being more afraid of crime because of their participation in crime? 2 0.3% 41 6. Does the participant mention being less afraid of crime because of their participation in crime? 13.9% 28 7. Does the participant mention their participation in crime has had no influence of their fear? 9.4% 19 N = only those who had the theme pr esent in their transcript

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150 Table 4 22 Altruistic Fear Themes (fear of family) % (Yes) N 1. Do they mention a family member being a previous victim of crime? 24.8% 50 a. Do they mention what type of crime it was? 21.8% 44 b. Does the participant ment ion which family member was a victim? 20.3% 41 2. Does the participant mention being afraid for their family member? 24.3 % 49 a. Do they mention the gender or age of the person they are afraid for? 23.3% 47 b. Do they mention the gender or age of the perso n they are not afraid for? 11.9% 24 c. Do they mention the relationship they have with the person they are afraid for or not afraid for? 21.8% 44 3. If they mention not being afraid for family members, do they mention why? 18.8% 38 4. Does the participant mention the gender or age of the family member as a reason for not being afraid for the family member? 19.8% 40 5. Does the participant mention being afraid for friends or roommates? 12.4% 25 6. Does the participant mention not being afraid for friends or r oommates? 8.4% 17 7. Does the participant mention being afraid for their family because of their participation in crime? 34.2% 69 8. Does the participant mention why they are afraid? 33.2% 67 9. Do they mention that their participation in crime has had no i nfluence on how afraid they are for their family? 7.4% 15 Table 4 23 Precautionary Behaviors Themes % (Yes) N 1. Does the participant mention types of crimes they are trying to protect themselves from? 82.7% 167 2. Does the participant sta te that they are not protecting themselves from any crime? 8.9% 18 3. Is there any mention of the things they do to protect themselves from crime? 86.1% 174 4. Is there any mention of the things they do to protect their family from crime? 17.3% 35 5. Do th ey mention that the things they do to protect themselves have helped keep them safe? 82.2% 166 6. Do they mention that these things have not helped keep them safe? 19.8% 40

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151 Table 4 2 4 Neighborhood Perceptions Themes % (Yes) N 1. Does the parti cipant describe their neighborhood? 97% 196 2. Does the participant mention the type of income in their neighborhood? 96.5% 195 3. Does the participant mention the level of education their neighbors or community members have? 95% 192 4. Does the participan t mention relying on their neighbors? 67.3% 136 5. Does the participant mention not relying on their neighbors for help ? 25.7% 52 6. Is there a mention of things they can rely on them for? 86.6% 175 7. Is there a mention of things they cannot rely on them for? 69.8% 141 8. Do they mention any physical attributes of their neighborhood? 23.8% 48 9. Do they mention any social attributes of their neighborhood or community? 26.2% 53 10. Is there a mention of how close they are to their neighbors? 20.3% 41

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152 CH APTER 5 DISCUSSION AND CONCL USION Summary of F indings Using data collected from semi structured interviews conducted with misdemeanant probationers, the present work examines the relationship between g patterns, perceptions of social disorganization, and precautionary behaviors. We also examined altruistic fear of crime among probationers. This section will discuss quantitative and qualitative findings from this study and address how such findings re late to the literature. Each research question will be discussed. Quantitative Finding Findings with regard to research question one focused on personal fear of crime among offenders. Regression analysis revealed gender to be an important predictor for g eneral fear of crime, fear of violent crime, fear of property crime, and fear of drug crime. For all types of personal fear, women were found to be significantly more fearful than men. Such findings were evident even after controlling for probationers offe nse history, current offense, and perceptions of social disorganization. This is consistent with the literature on fear of crime. Most (like Ferraro, 1995, Ferraro & LaGrange, 1992; Warr, 1984) have found that females tend to report higher levels of person al fear. In terms of offending populations Lane 2009, found that female offenders were no more likely than male offenders to indicate being fearful of cri me. Lane & Fox (forthcoming), found there to be significant differences among males and females who were non gang members, where females were more fearful of crime than males.

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153 Race has also been found to be a significant predictor of fear in the literature. The present study found that non whites were found to have more fear of crime than whites, but no t after accounting for other variables like offending history and social disorganization. Although the literature has mixed findings with regard to race, as discussed earlier, most studies have found that non whites tend to report higher fear levels than w hites (Lane & Meeker, 2003; Rader, et. al., 2007) In terms of age, older offenders were found to have more fear of drug crimes only. Age was not a significant predictor for other types of fear of crime (i.e. fear of violent crime, property crime, and gene ral fear of crime). Although the early research on fear argued that the elderly or older individuals experienced more fear, more recent studies have found that younger individuals tend to be more afraid ( Ferraro, 1996; Ferraro & Lagrange, 1992; Lane & Meek er, 2000; Rader, May, & Goodrum; Roundtree, 1998; Warr, 1994 ). This is an interesting finding, as it contradicts what the current research has found. However, age here ranges from 19 to 69, with most of the sample (79%) being between 9 and 47. So these fin dings do not necessarily imply that the elderly were more fearful, only that those who were older in the present sample experienced more fear. The present study was specifically interested in understanding the role that ear of crime. We found that seriousness of offense does not matter. So more serious offenders were not found to have more personal fear of crime than less serious offenders (or vice versa). Research question 1 asked: Does offending and participation in c rime affect

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154 while we found that generally, offenders do report being fearful of crime and specifically, females and minorities are more fearful of crime than males or white s offense s eriousness does not matter. R esearch question one then was not fully supported. Probationer s offense history mattered when predicting fear of drug crimes. Specifically, those offenders who have a history of public ordinance offenses are more fearful of drug crimes. We anticipated that non violent offenders would be more fearful than violent offenders. However, it was interesting that they were found to be fearful of drug crimes and not another type of fear of crime (like fear of violent c rime). While this is consistent with what we expected, those offenders who have a violent, property, or drug criminal history were not found to have fear. Probationers charged with property offenses were also found to be more likely to experience general fear of crime, as well as violent fear of crime. So the study showed that offense history and curre nt offense are not as important in predicting fear of crim e as was originally anticipated, but it may matter when predicting certain types of fear. With reg ard to social disorganization and fear of crime, probationer s perceptions of their communities did not have the anticipated impact on fear of crime. Neighborhood perceptions, which were measured by asking participants about social and physical disorder, collective efficacy, subcultural diversity, and residential mobility, seem to only matter when predicting general fear of crime. Interestingly, the only neighborhood variable that was significant was collective efficacy. It was found that probationers who reported more perceived collective efficacy in their neighborhoods expressed more general fear of crime. Although we did not expect to find a positive relationship between collective efficacy and fear of crime, this is not the first study to

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155 report such fi ndings. For example, Lane & Fox (forthcoming) found something similar when studying jail inmates. In terms of research question 2, it seems that neighborhood perceptions only mattered when predicting g eneral fear of crime and did not have a significant eff ect in predicting fear of violent crime, fear of property crime, or fear of drug crimes. Research question 3 asked about the precautionary behaviors that probationers use to cope with fear of crime. Specifically, we tried to examine the role that offending themselves. Multivariate analysis presented mixed findings. Findings show that for those who utilize defensive behaviors, the only significant more subcultural diversity, had a higher likelihood of using defensive measures to protect themselves (e.g. like a gun, knife, etc.) Again, this is not what researchers anticipated. It was originally hypothesized that those with more serious prior offense histories would defensive tools (like carrying a gun), rather than avoidance behaviors or target hardening, to cop e with crime. Here gender, age 1 race, offense history and participating in Such findings are contradictory to what has been fou nd in the research. B ased on the work by May (2001) and Lane (2009), we originally hypothesized that male probationers would be more likely to 1 Age is an interesting variable with regard to precautionary behaviors, as much of the research has not consistently found that older individuals are more fearful and therefore take more actions to protect themselves. Some have found that increased fear l evels among the elderly does not always mean there will be an increase in the use of precautionary behaviors (Liska, 1988).

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156 participate in defensive behaviors, yet we found that males were not more likely than females to participate in d efensive behaviors to protect themselves. This result also is not consistent based on what we know about the use of precautionary behaviors among offenders, Lane (2009) for example conducted a study among juvenile s who were institutionalized and found tha t a large percentage of males participated in defensive behaviors (like buying and securing a gun) and those females who did carry a weapon were carrying weapons other than a gun (Lane, 2009). Much of the literature on non offending populations has also fo und that males tend to be more inclined to use a gun or keep a gun at home to protect themselves, compared to women. While we found that some men and women indicated using defensive behaviors descriptively, it is minimal overall. Of the defensive behaviors asked about (carrying a weapon, buying a gun, and carrying a weapon other than a gun) most of those who stated participating in defensive behaviors reported carrying a weapon other than a gun. It is interesting that the only significant predictor (more th an fear of crime) is levels. It may be that a larger sample would provide us with a better understanding of the relationship between neighborhood perceptions, fear o f crime, and the With regard to avoidance behaviors used by probationers, gender was found to be significant. Based on our findings, females were more likely to report using avoidance behaviors than males (as was an ticipated). This is consistent with the work of Ferraro (1996) and others who have found consistently that females tend to not only be more fearful but also use avoidance behaviors when protecting themselves from crime or

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157 possible victimization. Lane (2009 ), found that among offenders, female s t ended to use avoidance behaviors. In terms of offending, those with more violent offenses in their criminal histories were less likely to use avoidance beh aviors in this sample. While we expected that those with mo re violent offenses would use defense behaviors to protect themselves because of the nature of the offenses they are committing, we did not find this when predictin g defensive behaviors (Table 4 18). Interestingly, personal fear of crime was not found to be a significant predictor, which was not anticipated as fear of crime has been found to have a strong positive correlation with precautionary behaviors (Ferraro, 1995, May, 1999, Rader, May, Goodrum, 2007). Finally, personal fear of crime was not found to be significant in predicting the use of avoidance behaviors. This was not consistent with what was anticipated or with the literature. One would anticipate that being fearful of crime would lead to the increased use of avoidance or defensive precautionar future victimization. Such findings could have resulted because the sample size in the present study (n=202) is so small. It could be that collecting more data on offending populations may help us better understand the role of offending, neighborhood perceptions, and fear of crime on the use of precautionary behaviors. Or it could be that they took precautionary behaviors and no longer feel afraid. No predictors were significant when p redicting the likelihood of using target hardening behaviors. So demographics (like race, gender, and age), offense history, current offense, social disorganization, and personal fear of crime were not able to predict the likelihood of using target hardeni ng behaviors. Although we anticipated many individuals to participate taking these actions, it seems that while some

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158 probationers indicated participating in some of these behaviors, there is not enough to find a significant effect. We would have expected m ost to engage in avoidance and/or target hardening behaviors (as Ferraro, 1995 notes). For example, Ferraro (1995) found that most participants either used avoidance behaviors or did things to protect their home (i.e. target hardening behaviors like adding locks to ones home and adding outside lighting). Few were noted to carry a gun or use defensive behaviors. It could economic status may reduce their ability to go out and buy materials that would protect them and their home. For example, previous work has found that income and precautionary behaviors are positively related (so those who have more money are able to afford an alarm system or extra lighting), and that defensive or avoidanc e behaviors are more common among those who have a lower socio economic status (Roundtree & Land, 1996; Vacha & McLaughlin, 2004). This may be an important variable to account for in the future. It may be that offender s use of precautionary behaviors is for different reasons than the general population. More research help shed light on this particular While Lane (2006, 2009) found that among offenders, those more involved in crime seem to not have higher fear levels as one would anticipate and that its t hose who have less involvement that report higher fear levels. It could be that, as Lane (2006) suggest having a comparison group of non offenders would help us better understand what role participation in crime has on fear of crime as well as the precauti onary behaviors taken. Qualitative Findings Although we hoped that the interviews would provide us with greater insight on fear of crime among offenders, qualitative interviews revealed that offending does not crime. Interestingly, we found that for some

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159 participants participation in crime actually reduced their fear of crime because they felt more aware of crime and those around them who commit crime. Those who did say they were fearful because of their partic ipation in crime said this was due to feeling that their offending put them in a position where they can be more easily victimized or more visible to other offenders. Specifically, many probationers who reported being afraid talked about being afraid of pr operty crimes rather than being fearful of drug crimes or violent crimes. Many of these individuals were also those who had a history of being a public ordinance offender. Those who were on probation for violent offenses tended to talk about how they were less afraid of crime or that their offending had no effect on their fear. These qualitative findings on personal fear of crime support our quantitative findings that although probationers indicate being fearful of crime, offending may not matter in terms o f making one more fearful of crime. Interestingly, we did find an interesting perspective on the offending and fear relationship, which should be further examined in future work. Qualitative interviews on altruistic fear also presented some interesting fi ndings. Interestingly, few participants who indicated being fearful for family specifically mentioned that altruistic fear was not driven by their offending history. As others, like Warr (1992) and Snedker (2005) have found, many indicated being fearful f or their children or older family members. With regard to precautionary or constraining behaviors probationers participate in to protect themselves from crime and victimization, we can see that probationers use many techniques to protect themselves from c rime. Although descriptive statistics show that few offenders indicated using p recautionary behaviors (Table 4 13), qualitative

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160 findings show something different. From the interviews, as shown above, we found that many mentioned trying to protect themselve s from some type of crime. Probationers mentioned participating in avoidance behaviors, defensive and target hardening behaviors. Interestingly, some probationers mentioned that they participated in several types of behaviors, combining different types (i. e. using both defensive and target hardening behaviors). Finally, we also found that many felt that taking these actions to protect themselves actually helped keep them safe from being victimized. So while quantitatively we were unable to determine the rol e that precautionary behaviors play in from being victimized (even though they participate in crime themselves). Finally, interviews helped us also understand the neig hborhood that probationers were coming from. Many probationers talked about being able to trust and rely on their neighbors and few mentioned the presence of violent or more severe crimes in their neighborhoods. Some talked about the presence of physical a nd social disorder in their communities, but most mentioned few things like a little vandalism or kids drinking. When participants were asked if these things had an impact on their fear, few noted such neighborhood perceptions to have had an impact on thei r fear of crime. The findings in this study presents some important findings and some findings that should be taken and expanded on in future work so that we may better understand the role of fear among offenders. Study Limitations a nd Suggestions For F uture Research While this study presented important findings on fear among offending populations, there are some limitations to the current work that can be expanded upon

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161 in future research on fear of crime. This section will present the limitations of thi s study and present some suggestions for future research. The first limitation is the sample size. Although researchers hoped to achieve a larger sample, we were only able to obtain interviews from 202 probationers. This limited the types of analysis of some variables (like altruistic fear). While we originally made an effort to randomly sample from the total population of probationers (in order to have a more generalizable sample and findings), it may be helpful to either open the study to all or sample from a larger population of offenders. Future work should try to increase the sample size substantially, and if possible, try to obtain a comparison group of non offenders so that we can examine differences among fear across the two groups (as suggested b y Lane, 2009 in her study among juvenile probationers). It would also be interesting to see variations across jail inmates or prison inmates, probationers (who serve their sentence in the community), and non offenders. This may help us better understand no t only variations in fear levels but may help us better examine the role that offending or offense seriousness plays on fear of crime. Something that was found throughout the study was the importance of gender in fear of crime among offenders 2 especiall y with regard to the use of precautionary behaviors. In fact, this was the one of the only significant predictors across the three types of the precautionary behaviors examined. As such, it is critical for future research to unravel the relationship betwee n gender and fear among offenders. This is something 2 Ferraro (1995) notes that women often indicate being fearful of crime because they are fearful of rape and fear of rape is a main 98). This is usually because of the possibility of rape when a nonsexual crime occurs (Ferraro, 1995: pg. 94). As such, in order to examine fear of crime among women the degree for non sexual crimes compared to sexual assault should be examined in future work as well.

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162 that I plan to do in future work with the present data set but should also be studied in future studies looking at fear among offenders. Another limitation could be the fact that most participants in th e present study were on probation for misdemeanant offenses (like public ordinance offenses that include DUI and domestic battery). That is, they may not be immersed in the criminal lifestyle. A suggestion for future work may be to obtain a sample of more serious offenders, like felony probation or jail inmates. This may help us understand or reveal some important relationships between offending history and fear of crime. Additionally, there may have been the possibility of self report issues during the d ata collection process. While we collected both official and self report data, self report often allows researchers capture those offenses participants were not arrested or convicted of. Many have noted offenders to accurately report their offense history, and have suggested providing confidentiality and anonymity as mechanisms to increase the accuracy of self report (Peterson, Braiker, & Polich, 1981). While researchers did this and reinforced that their participation and responses were confidential, there is always the possibility of over and under reporting of offense data and, in this case, the type of precautionary behaviors they use (i.e. admit to carrying or owning a gun), which may have affected our findings. Some probationers may have felt hesitant to give this information from fear of being violated and being sent back to jail. Again, researchers in the present study made all efforts to ensure that participants felt comfortable reporting the truth, but it is difficult to know if all who did this aga inst the probation conditions were willing to divulge it.

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163 In terms of the variables used for analysis, the present study did not include an income variable, which in future studies may allow researchers to understand the effects of income on the precaut ionary behaviors used by participants. Moreover, due to the fact that the data were collected on probationers who lived in a community that is close to a university, there may have been college students in the sample. We did not have variable that had the participant indicate if they were a current student or not, this is a variable that should be included in future work. Also, future work should focus on better understanding the role of altruistic fear among offenders. The present study did not ask partici pants specifically what crimes they were fearful for their families. As Warr (2000) suggested, future work should also ask offense specific altruistic fear of crime questions. The present study also did not have a question that asked probationers what prec autionary behaviors they take to protect their families. This would have been beneficial to fully understand altruistic fear among offenders. It is also important to better understand the gender differences present in altruistic fear and try to understand the role that gender and age plays in altruistic fear. It seems that offenders are reporting fear for themselves and for their families, it would be beneficial to continue this line of research so that we can better understand these relationships. Study i mplications The current study is mainly exploratory and has limited findings, so we are unable to discuss specific or direct policy implications that result from this study specifically. However, based on what we did find, this section will discuss propose d implications that may be possible if certain relationships are further examined in future works. In terms of personal fear of crime, although we do not have a comparison group of non offenders, it may be that offenders experience fear the same way that non

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164 offending individuals do. If so, policy makers should consider offenders fear similar to non offending populations. However, if future work discovers that offending plays a role in personal fear of crime levels among offenders, policies should work to ensure that they not only address both fear of crime among those who are law abiding and provide modified policies for those who have a history of offending so that their needs may be met as well. When looking at altruistic fear of crime, we found that pr obationers do report altruistic fear. Similar to personal fear, altruistic fear may lead to consequences that not only affect the precautionary behaviors one takes but may also have an impact ating in more extreme actions to protect themselves and their families from victimization (more severe than those actions they would take to protect themselves). This is an important dynamic of policy makers to consider, as family may play an influential r ole fear and reactions to fear. Finally, gender was an important significant predictor when looking at avoidance behaviors used by offenders. Like women in the general population, female offenders were found to be more likely to report using avoidance beh aviors than male offenders (Ferraro, 1995; Lane, 2009). Policymakers should take into account and better understand fear among female offenders in the creation of policy. Policymakers should consider all of these variables so they can create policies that reduce public fear (both among offenders and non offenders), and ensure that individuals are adequately protecting themselves from possible victimization (and not overly constraining their behaviors).

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165 APPENDIX A COURT SERVICES APPRO VAL

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166

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167 APPENDIX B IRB APPROVAL

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168 APPENDIX C LETTER SE NT TO PROBATIONERS

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169 APPENDIX D REVISED LETTER TO PR OBATIONERS Division of Criminology, Law, & Society 3323 Turlington Hall, P. O. Box 117330 College of Liberal Arts and Sciences Gainesville, FL 32611 7330 (352) 392 0265 TEL (352) 392 6568 FAX Dear Mr. /Ms. _______________________ We are Saskia Santos and Katheryn Zambrana, and we are currently students at the University of o participate in conditions they are required to complete, as well as issues surrounding fear of crime and the community. Specifically, we would like to see wha t you think of the conditions of your probation and how you view crime. This study is completely separate from Court Services and the probation staff. Participation is voluntary, so if you decide not to take part in the study it will NOT affect your pro bation status. There is no cash incentive for participating. However, if you choose to participate you are eligible to receive 5 hours of community service credit. If you are not required to c omplete community service hours, you will be eligible for 1 mont h cost of supervision credit You are only eligible for one of the credit options. If you would like to set up an interview please c ontact e ither: Saskia Santos Katheryn Zambrana Supervisor: Jodi Lane, Ph.D. The interview should last about one hour. During the interview we will ask questions, some of which will be tape recorded, in order to better understand your experiences with being on probation and a member of the community. Your answers will be confidential and private. Only the researchers know what you said. If you have any questions or concerns p lease feel free to contact us via phone or e mail. Thank you and we look forward to hearing from you! Sincerely, Saskia Santos Katheryn Zambrana

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170 APPENDIX E PARTICIPAN T BENEFITS APPROVAL

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171

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172 APPENDIX F CRIMINAL HISTORY FOR M Criminal History Form Cover Sheet Note: Upon completing this form please remove this cover page from the criminal history form a nd place it in the designated envelope

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173 1. Subject Number: _________________ Criminal History Form 2. Researcher (enter name): ______________ 3.Criminal history retrieved: _____________ ____( mm/dd/yy) 4. Criminal history form completed : _____ ______ ____ ( mm/dd/yy) 5. Date of birth : ___________ ______ ( mm/dd/yy) 6. Sex (circle one) : Male 1 Female 0 7. Race (circle one) : White 1 Black/African American 2 Other Specify______________________ Criminal history: Use additional form if more space is needed Offense: copy verbatim each offense in the order it appears on the criminal record a. Degree: list if 1,2,3 degree and M if misdemeanor and F if felony b. State: list state where occurred c. Case number (number cases in order) d. Date Arrest ed e. Outcome: code 1=probation, 2= jail days, 3= prison time, 4= case dropped, 5= other f. Details: if outcome was: 1 or 3= list sentence in mos, 2= list days, 4= specify other 8.________________________ ___________ _______ ______ ____ ______________ __ _______________ 9.________________________ ___________ _______ ______ ____ ______________ _________________ 10._______________________ ___________ _______ ______ ____ ______________ _________________ 11._______________________ ___________ _______ ______ ____ ______________ _________________ 12._______________________ ___________ _______ ______ ____ ______________ _________________ 13._______________________ ___________ _______ ______ ____ ______________ _________________ 14._______________________ ___ ________ _______ ______ ____ ______________ _________________ 15._______________________ ___________ _______ ______ ____ ______________ _________________ 16._______________________ ___________ _______ ______ ____ ______________ _________________ Current Offense: Circle yes or no and complete column a Yes No a. Case number(s): if yes, list case number 17. Possession of marijuana not more than 20 grams 1 0 _____________________________ 18. Alcohol possession by person under 21 years of age 1 0 __________ ___________________ 19. Driving under the influence of alcohol 1 0 _____________________________ 20. Driving while license suspended or revoked 1 0 _____________________________ 1 0 _____________________________ 22. Crimin al mischief over 200 dollars under 1000 dollars 1 0 _____________________________ 23. Larceny: petit first degree property 100 to under 300 dollars 1 0 _____________________________ 24. Retail theft 1 0 _____________________________ 25. Worthless check 1 0 _____________________________ 26. Trespass 1 0 _____________________________ 27. Resisting or obstruct officer without violence 1 0 _____________________________ 28. Battery: touch or strike 1 0 _____________________________ 29. Domestic battery: touch or strike 1 0 _____________________________ 30. Other (specify___________________________________) 1 0 _____________________________

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174 Current Offense: Circle yes or no and complete column a Yes No a. Case number(s): if yes, list case number 31. Othe r (specify___________________________________) 1 0 _____________________________ 32. Other (specify___________________________________) 1 0 _____________________________ 33. Other (specify___________________________________) 1 0 _________________________ ____ 34. Other (specify___________________________________) 1 0 _____________________________ 35. Length of current probation sentence: __________months 36. Expected probation termination date: ___________ ______ ( mm/dd/yy) New law violation: copy ve rbatim the offense in order offense occurred and complete columns a, b and c a. Date: list date of offense by mm/dd/yy b. Outcome: code 1=extended sentence, 2= additional condition(s), 3=days in jail, 4=other c. Details: if outcome was: 1= list term, if 2 = list condition, if 3= how many days, if 4= specify other 37.__________________________ ___________ ________________ _________________________ 38.__________________________ ___________ ________________ _________________________ 39._____________________ _____ ___________ ________________ _________________________ 40. __________________________ ___________ ________________ _________________________ 41. __________________________ ___________ ________________ _________________________ 42. ________________ __________ ___________ ________________ _________________________ 43. __________________________ ___________ ________________ _________________________ Types of technical violations: if technical violation occurred complete columns a, b and c a. Number of v iolations: indicate number b. Outcome: code 1=extended sentence, 2= additional condition(s), 3=days in jail, 4= other c. Details: i f outcome was: 1= list term, if 2= list condition, if 3= how many days, if 4= specify other 44. Report to probation office o nce a month ________ ____________ ______________ 45. Answer truthfully to inquiries by PO ________ ____________ ______________ 46. Notify PO of changes in residence ________ ____________ ______________ 47. Notify PO of changes employment/education _____ ___ ____________ ______________ 48. Try to obtain employment ________ ____________ ______________ 49. Maintain employment/school enrollment ________ ____________ ______________ 50. Allow PO to visit residence ________ ____________ ______________ 51. Allow PO to visit employment site ________ ____________ ______________ 52. Pay monthly cost of supervision ________ ____________ ______________ 53. Pay court cost ________ ____________ ______________ 54. Complete community service (CS) hours in lieu of fees ________ ____________ ______________ 55. Complete mandatory CS hours ________ ____________ ______________ 56. Complete work crew days ________ ____________ ______________ 57. Complete a jail sentence ________ ____________ ______________

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175 Types of t echnical violations: if technical violation occurred complete columns a, b and c a. Number of violations: indicate number b. Outcome: code 1=extended sentence, 2= additional condition(s), 3=days in jail, 4= other c. Details: i f outcome was: 1= list term, if 2 = list condition, if 3= how many days, if 4= specify other 58. Pay restitution ________ ____________ ______________ 59. Submit to random screens (breathalyzer/urinalysis) ________ ____________ ______________ 60. Do not possess or consume alcohol ______ __ ____________ ______________ 61. Do not possess or consume illegal drugs ________ ____________ ______________ 62. Participate in alcohol treatment ________ ____________ ______________ 63. Participate in drug treatment ________ ____________ __________ ____ 64. Participate in mental health treatment ________ ____________ ______________ 65. Participate in employment program ________ ____________ ______________ 66. Complete Milepost class ________ ____________ ______________ 67. Complete DART program _______ ____________ ______________ ________ ____________ ______________ 69. Complete anger management ________ ____________ ______________ 70. No contact with victim ________ ____________ ______________ 71. Attend alcohol safety education school ________ ____________ ______________ 72. Attend 1 victim impact panel ________ ____________ ______________ 73. Drivers license (DL) suspended/revoked ________ ____________ ______________ 74. Abide with order of im poundment ________ ____________ ______________ 75. Abide by curfew ________ ____________ ______________ 76. Other (_____________________________) ________ ____________ ______________ 77. Other (_____________________________) ________ ____________ ______ ________ 78. Other (_____________________________) ________ ____________ ______________ 79. Other (_____________________________) ________ ____________ ______________ 80. Other (_____________________________) ________ ____________ ______________ Probat ion conditions: circle one and specify where applicable Yes Specify No 81. Commit no new law violation 1 0 82. Report to probation office once a month 1 0 83. Answer truthfully to inquiries by probation officer 1 0 84. Notify PO of changes in resid ence 1 0 85. Notify PO of changes in employment/education 1 0 86. Try to obtain employment 1 0 87. Maintain employment/school enrollment 1 0

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176 Probation conditions: circle one and specify where applicable Yes Specify No 88. Allow PO to visit resid ence 1 0 89. Allow PO to visit employment site 1 0 90. Pay monthly cost of supervision (specify amount) 1 $_________ 0 91. Pay court cost (specify amount) 1 $_________ 0 92. Complete CS hours in lieu of fees (specify hours) 1 _________hrs 0 93. C omplete mandatory CS hours (specify hours) 1 _________hrs 0 94. Complete work crew days (specify days) 1 ________days 0 95. Complete a jail sentence (specify days) 1 ________days 0 96. Pay restitution (specify amount) 1 $_________ 0 97. Submit to rand om screens (breathalyzer and urinalysis) 1 0 98. Do not possess or consume alcohol 1 0 99. Do not possess or consume illegal drugs 1 0 100. Participate in alcohol treatment 1 0 101. Participate in drug treatment 1 0 102. Participate in mental h ealth treatment 1 0 103. Participate in employment program 1 0 104. Complete Milepost class 1 0 105. Complete DART program 1 0 1 0 107. Complete anger management 1 0 108. No contact with victim 1 0 109. Attend alcohol safety education school 1 0 110. Attend 1 victim impact panel 1 0 111. Drivers license (DL) suspended/revoked (specify months) 1 ________mos 0 112. Abide with order of impoundment 1 0 113. Abide by curfew 1 0 114. Other (spe cify________________________________) 1 0 115. Other (specify________________________________) 1 0 116. Other (specify________________________________) 1 0 117. Other (specify________________________________) 1 0 118. Other (specify________________ ________________) 1 0

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177 APPENDIX G INFORMED CONSENT

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178

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179 APPENDIX H SURVEY INSTRUMENT AN IN DEPTH STUDY OF SUPER VISED PROBATIONERS I N ALACHUA COUNTY TO BE COMPLETED BY INTERVIEWER: Interview Number: Consent Date: (dd/mm/ yy) Date of Interview: (dd/mm/yy) Location of Interview: Interviewer Name: Time Interview Began: AM PM Time Interview Ended: AM PM Date Criminal History Retrieved: (dd/mm/yy) Date Criminal History Form Completed: (dd/mm/yy) Please use the extra sheets of paper provided for any additional notes if the space provided on the instrument in not enough. When taking notes be sure to indicate the question number.

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180 [Read] First, I am going to ask you some questions about you. Code Number 1. How long have you lived in your neighborhood? _________ (circle: days, mos, yrs) 2. What type of place do you live in? (Read options & circle one) (Ferraro, 1995) Single family house 1 An apartment 2 A duplex 3 A condomin ium 4 A trailer house 5 A rooming house 6 Other Specify ________________ DK 98 RF 99 3. How would you define your neighborhood? (Read options & circle one) The block you live on 1 The blocks around your home 2 Your housing development 3 (Lane, e t al., 1997) A section of your city 4 Your county 5 Other Specify ____________ DK 98 RF 99 4. How long have you lived at your current residence? (enter number and circle) ____________________ days/ mos/ yrs DK 98 RF 99 5. How many people live in your household? (enter number) _______________________ DK 98 RF 99 6. Do you have children? (circle one) (If no, skip to #9) Yes 1 No 0 DK 98 RF 99 7. How many children do you have? (enter number) ____________________ DK 9 8 RF 99 8. Do your children (or child) live with you? (circle one) Yes 1 No 0 DK 98 RF 99 9. What is your current marital status? (circle one) (do not read answer options) Married 1 Widowed 2 Divorced 3 Separated 4 Never married 5 Living with a par tner 6 DK 98 RF 99 10. How would you describe your race? (circle one) (do not read answer options) White 1 Black/African American 2 Other Specify_____________ DK 98 RF 99 11. How would you describe your ethni city? (circle one) (do not read answer options) Hispanic 1 Non Hispanic 0 DK 98 RF 99 12. What is your current employment status? (circle one) (do not read answer options) Full time 1 Part time 2 Not employed 3 Other Specify__________ DK 98 RF 99

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181 13. What is highest level of education you have obtained? (circle one) (do not read answer options) 9 th Grade 9 10 th grade 10 11 th grade 11 High school 12 GED 13 Some college 14 Other Spec ify_____________ DK 98 RF 99 [Read] Now I am going to ask you some questions about you being on probation 14. How long is your probation sentence? (enter number) ____________________mos DK 98 RF 99 15 How much of your probation sentence have you served? (enter number) ____________________mos DK 98 RF 99 16. Did you receive probation as the result of a plea agreement? (circle one) Yes 1 No 0 DK 98 RF 99 What are the charge(s) that you are serving probation for ? (circle yes or no) (do not read answer options) Yes No 17. Possession or use of drug paraphernalia 1 0 18. Possession or use of narcotic equipment 1 0 19. Possession of marijuana not more than 20 grams 1 0 20. Alcohol possession by person under 21 years of age 1 0 21. D riving under the influence of alcohol 1 0 22. Driving while license suspended or revoked 1 0 1 0 24. Criminal mischief over 200 dollars under 1000 dollars 1 0 25. Larceny: petit first degree property 100 to under 300 dollars 1 0 26. Retail theft 1 0 27. Worthless check 1 0 28. Trespass 1 0 29. Resisting or obstruct officer without violence 1 0 30. Battery: touch or strike 1 0 31. Domestic battery: touch or strike 1 0 32. Other (specify____________________ ____________________) 1 0 33. Other (specify________________________________________) 1 0 34. Other (specify________________________________________) 1 0 35. Other (specify________________________________________) 1 0

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182 36. Have you received any viola tions for this sentence? (circle one) (If no, skip to #82) Yes 1 No 0 DK 98 RF 99 Was the violation a new law violation? (If yes, list verbatim the offense in the order the offense occurred and complete columns a, b and c) (If no, skip to #44) a. Date (ind icate the date that the offense by mm/dd/yy). b. Outcome (code the outcome of the violation: 1= extended probation sentence, 2= additional condition(s), 3= days in jail, 4= other) c. Details (explain each condition. If 1 list new term, if 2 list new condition if 3 how many days, if 4 specify other) 37. ______________________________ ______________ ____________ ______________________ 38. ______________________________ ______________ ____________ ______________________ 39. ______________________________ __ ____________ ____________ ______________________ 40. ______________________________ ______________ ____________ ______________________ 41. ______________________________ ______________ ____________ ______________________ 42. ____________________________ __ ______________ ____________ ______________________ 43. ______________________________ ______________ ____________ ______________________ Was the violation a technical violation? (If yes, list verbatim the offense in the order the offense occurred and complete columns a, b and c) (do not read answer options) (If no, skip to #82) a. Number of times it occurred (indicate number) b. Outcome (code outcome of the violation: 1= extended probation sentence, 2= additional condition(s), 3= days in jail, 4= other) c. Det ails (explain each condition. If 1 list new term, if 2 list new condition, if 3 how many days, if 4 specify other) 44. Report to probation office once a month __________ _____________ ___________________ 45. Answer truthfully to inquiries by probatio n officer __________ _____________ ___________________ 46. Notify PO of changes in your residence __________ _____________ ___________________ 47. Notify PO of changes in your employment/education __________ _____________ ___________________ 48. Try to obtain employment __________ _____________ ___________________ 49. Maintain employment/school enrollment __________ _____________ ___________________ 50. Allow PO to visit your residence __________ _____________ ___________________ 51. Allow PO to vi sit your employment site __________ _____________ ___________________ 52. Pay monthly cost of supervision __________ _____________ ___________________ 53. Pay court cost __________ _____________ ___________________ 54. Complete CS hours in lieu of fees __________ _____________ ___________________ 55. Complete mandatory CS hours __________ _____________ ___________________ 56. Complete work crew days __________ _____________ ___________________ 57. Complete a jail sentence __________ _____________ ___ ________________ 58. Pay restitution __________ _____________ ___________________ 59. Submit to random screens __________ _____________ ___________________ 60. Do not possess or consume alcohol __________ _____________ ___________________

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183 Was the vio lation a technical violation? (If yes, list verbatim the offense in the order the offense occurred and complete columns a, b and c) (do not read answer options) a. Number of times it occurred (indicate number) b. Outcome (code outcome of the violation: 1= exten ded probation sentence, 2= additional condition(s), 3= days in jail, 4= other) c. Details (explain each condition. If 1 list new term, if 2 list new condition, if 3 how many days, if 4 specify other) 61. Do not possess or consume illegal drugs __________ _____________ ___________________ 62. Participate in alcohol treatment __________ _____________ ___________________ 63. Participate in drug treatment __________ _____________ ___________________ 64. Participate in mental health treatment __________ __ ___________ ___________________ 65. Participate in employment program __________ _____________ ___________________ 66. Complete Milepost class __________ _____________ ___________________ 67. Complete Daily Alternative Reporting Tracking (DART) program __________ _____________ ___________________ __________ _____________ ___________________ 69. Complete anger management __________ _____________ ___________________ 70. No contact with victim __________ ____ _________ ___________________ 71. Attend alcohol safety education school __________ _____________ ___________________ 72. Attend 1 victim impact panel __________ _____________ ___________________ 73. Drivers license (DL) suspended/revoked __________ ___ __________ ___________________ 74. Abide with order of impoundment __________ _____________ ___________________ 75. Abide by curfew __________ _____________ ___________________ 76. Other (_________________________________) __________ _____________ _____ ______________ 77. Other (_________________________________) __________ _____________ ___________________ 78. Other (_________________________________) __________ _____________ ___________________ 79. Other (_________________________________) __________ _____________ ___________________ 80. Other (_________________________________) __________ _____________ ___________________ 81. Other (_________________________________) __________ _____________ ___________________ [Read] I am going to ask about c riminal sanctions and whether you have been sentenced to them in the past. Please indicate whether you have by answering yes or no. Yes If yes, indicate length of time served (circle one) No DK RF 82. Probation (prior to current sentence) 1 ___________ ___________mos/yrs 0 98 99 83. Intensive supervision probation 1 ______________________mos/yrs 0 98 99

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184 Yes If yes, indicate length of time served (circle one) No DK RF 84. Jail 1 ______________________mos/yrs 0 98 99 85. Prison 1 ___________________ ___mos/yrs 0 98 99 86. Day reporting 1 ______________________mos/yrs 0 98 99 87. Electronic monitoring 1 ______________________mos/yrs 0 98 99 88. Boot camp 1 ______________________mos/yrs 0 98 99 (If no to having served a prior sentence of probation skip to #134 ) 89. Did you receive any violations for your prior probation sentence(s)? (circle one) (If no, skip to #134) Yes 1 No 0 DK 98 RF 99 Was the violation a new law violation? (If yes, list verbatim the offense in the order the offense occur red and complete columns a, b and c) (If no, skip to #97) a. Date (indicate the date that the offense by mm/dd/yy). b. Outcome (code the outcome of the violation: 1= extended probation sentence, 2= additional condition(s), 3= days in jail, 4= other) c. Details (ex plain each condition If 1 list new term, if 2 list new condition, if 3 how many days, if 4 specify other) 90.______________________________ ______________ ____________ ______________________ 91. ______________________________ ______________ ________ ____ ______________________ 92. ______________________________ ______________ ____________ ______________________ 93.______________________________ ______________ ____________ ______________________ 94. ______________________________ ______________ ____ ________ ______________________ 95. ______________________________ ______________ ____________ ______________________ 96. ______________________________ ______________ ____________ ______________________ Was the violation a technical violation? (If yes, list verbatim the offense in the order the offense occurred and complete columns a, b and c) (do not read answer options) (If no, skip to #134) a. Number of time it occurred (indicate number) b. Outcome (code outcome of the violation: 1= extended probation sen tence, 2= additional condition(s), 3= days in jail, 4= other) c. Details (explain how each condition was. If 1 list new term, if 2 list new condition, if 3 how many days, if 4 specify other) 97. Report to probation office once a month __________ ________ _____ ___________________ 98. Answer truthfully to inquiries by PO __________ _____________ ___________________ 99. Notify PO of changes in your residence __________ _____________ ___________________ 100. Notify PO of changes in your employment/educatio n __________ _____________ ___________________ 101. Try to obtain employment __________ _____________ ___________________ 102. Maintain employment/school enrollment __________ _____________ ___________________ 103. Allow PO to visit your residence __ ________ _____________ ___________________

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185 Was the violation a technical violation? (If yes, list verbatim the offense in the order the offense occurred and complete columns a, b and c) (do not read answer options) (If no, skip to #134) a. Number of time it occurred (indicate number) b. Outcome (code outcome of the violation: 1= extended probation sentence, 2= additional condition(s), 3= days in jail, 4= other) c. Details (explain how each condition was. If 1 list new term, if 2 list new condition, if 3 how man y days, if 4 specify other) 104. Allow PO to visit your employment site __________ _____________ ___________________ 105. Pay monthly cost of supervision __________ _____________ ___________________ 106. Pay court cost __________ _____________ ________ ___________ 107. Complete CS hours in lieu of fees __________ _____________ ___________________ 108. Complete mandatory CS hours __________ _____________ ___________________ 109. Complete work crew days __________ _____________ ___________________ 110 Complete a jail sentence __________ _____________ ___________________ 111. Pay restitution __________ _____________ ___________________ 112. Submit to random screens __________ _____________ ___________________ 113. Do not possess or consume alcohol __________ _____________ ___________________ 114. Do not possess or consume illegal drugs __________ _____________ ___________________ 115. Participate in alcohol treatment __________ _____________ ___________________ 116. Participate in drug treatment __________ _____________ ___________________ 117. Participate in mental health treatment __________ _____________ ___________________ 118. Participate in employment program __________ _____________ ___________________ 119. Complete Milepost class ____ ______ _____________ ___________________ 120. Complete DART program __________ _____________ ___________________ __________ _____________ ___________________ 122. Complete anger management __________ _______ ______ ___________________ 123. No contact with victim __________ _____________ ___________________ 124. Attend alcohol safety education school __________ _____________ ___________________ 125. Attend 1 victim impact panel __________ _____________ _____ ______________ 126. Drivers license (DL) suspended/revoked __________ _____________ ___________________ 127. Abide with order of impoundment __________ _____________ ___________________ 128. Abide by curfew __________ _____________ ___________________ 129. Other (_________________________________) __________ _____________ ___________________ 130. Other (_________________________________) __________ _____________ ___________________ 131. Other (_________________________________) __________ ____________ ___________________ 132. Other (_________________________________) __________ _____________ ___________________ 133. Other (_________________________________) __________ _____________ ___________________

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186 [Read] Now I want to ask you more specific que stions about your current probation and your views on the severity of the conditions. I am going to list possible conditions of probation. Please indicate whether they apply to you by answering yes or no. (circle one and specify where applicable) Yes Spe cify No DK RF 134. Commit no new law violation 1 0 98 99 135. Report to probation office once a month 1 0 98 99 136. Answer truthfully to inquiries by probation officer 1 0 98 99 137. Notify PO of changes in your residence 1 0 98 99 138. Notify P O of changes in your employment/education 1 0 98 99 139. Try to obtain employment 1 0 98 99 140. Maintain employment/school enrollment 1 0 98 99 141. Allow PO to visit your residence 1 0 98 99 142. Allow PO to visit your employment site 1 0 98 9 9 143. Pay monthly cost of supervision (specify amount) 1 $_______ 0 98 99 144. Pay court cost (specify amount) 1 $_______ 0 98 99 145. Complete CS hours in lieu of fees (specify hours) 1 _______hrs 0 98 99 146. Complete mandatory CS hours (specify h ours) 1 _______hrs 0 98 99 147. Complete work crew days (specify days) 1 _______days 0 98 99 148. Complete a jail sentence (specify days) 1 _______days 0 98 99 149. Pay restitution (specify amount) 1 $_______ 0 98 99 150. Submit to random screens (bre athalyzer and urinalysis) 1 0 98 99 151. Do not possess or consume alcohol 1 0 98 99 152. Do not possess or consume illegal drugs 1 0 98 99 153. Participate in alcohol treatment 1 0 98 99 154. Participate in drug treatment 1 0 98 99 155. Partic ipate in mental health treatment 1 0 98 99 156. Participate in employment program 1 0 98 99 157. Complete Milepost class 1 0 98 99 158. Complete DART program 1 0 98 99 1 0 98 99 160. Complete anger ma nagement 1 0 98 99 161. No contact with victim 1 0 98 99 162. Attend alcohol safety education school 1 0 98 99

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187 (circle one and specify where applicable) Yes Specify No DK RF 163. Attend 1 victim impact panel 1 0 98 99 164. Drivers license (DL) s uspended/revoked (specify months) 1 _______mos 0 98 99 165. Abide with order of impoundment 1 0 98 99 166. Abide by curfew 1 0 98 99 167. Other (specify______________________________) 1 0 98 99 168. Other (specify______________________________) 1 0 98 99 169. Other (specify______________________________) 1 0 98 99 170. Other (specify______________________________) 1 0 98 99 171. Other (specify______________________________) 1 0 98 99 172. Other (specify______________________________) 1 0 98 99 173. [Read] Are there any conditions which I have not asked you about, but that you are required to complete or adhere to? If so, what are they? [Read] I am going to ask you to the rate the severity of the conditions of your probation. The response options are not severe, somewhat severe, severe and extremely severe (Hand participant red answer card) (Read all the conditions and circle the answer option the participant selected, next turn tape recorder on and read column a and column b) (for all c onditions circle one and then complete columns a and b with tape recorder on) Not severe Somewhat severe Severe Extremely severe DK RF a. Why do you feel the condition is severe? (ask of each one coded 4) b. Why do you feel the condition is not severe? (ask of each one coded 1) 174. Commit no new law violation 1 2 3 4 98 99 _______________ _______________ 175. Report to probation once a month 1 2 3 4 98 99 _______________ _______________ 176. Answer truthfully to inquiries by PO 1 2 3 4 98 99 _____________ __ _______________ 177. Notify PO of changes in residence 1 2 3 4 98 99 _______________ _______________ 178. Notify PO of changes in employment/education 1 2 3 4 98 99 _______________ _______________

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188 (for all conditions circle one and then complete colu mns a and b with tape recorder on) Not severe Somewhat severe Severe Extremely severe DK RF a. Why do you feel the condition is severe? (ask of each one coded 4) b. Why do you feel the condition is not severe? (ask of each one coded 1) 179. Try to obtain employment 1 2 3 4 98 99 _______________ _______________ 180. Maintain employment/school enrollment 1 2 3 4 98 99 _______________ _______________ 181. Allow PO to visit residence 1 2 3 4 98 99 _______________ _______________ 182. Allow PO to visit em ployment site 1 2 3 4 98 99 _______________ _______________ 183. Pay monthly COS 1 2 3 4 98 99 _______________ _______________ 184. Pay court costs 1 2 3 4 98 99 _______________ _______________ 185. Complete CS hours in lieu of fees 1 2 3 4 98 99 ______ _________ _______________ 186. Complete mandatory CS hours 1 2 3 4 98 99 _______________ _______________ 187. Complete work crew days 1 2 3 4 98 99 _______________ _______________ 188. Complete a jail sentence 1 2 3 4 98 99 _______________ ____________ ___ 189. Pay restitution 1 2 3 4 98 99 _______________ _______________ 190. Submit to random screens 1 2 3 4 98 99 _______________ _______________ 191. Do not possess or consume alcohol 1 2 3 4 98 99 _______________ _______________ 192. Do not posses s or consume illegal drugs 1 2 3 4 98 99 _______________ _______________ 193. Participate in alcohol treatment 1 2 3 4 98 99 _______________ _______________ 194. Participate in drug treatment 1 2 3 4 98 99 _______________ _______________ 195. Participa te in mental health treatment 1 2 3 4 98 99 _______________ _______________ 196. Participate in employment program 1 2 3 4 98 99 _______________ _______________ 197. Complete Milepost class 1 2 3 4 98 99 _______________ _______________ 198. Complete DAR T program 1 2 3 4 98 99 _______________ _______________

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189 (for all conditions circle one and then complete columns a and b with tape recorder on) Not severe Somewhat severe Severe Extremely severe DK RF a. Why do you feel the condition is severe? (ask of each one coded 4) b. Why do you feel the condition is not severe? (ask of each one coded 1) Intervention 1 2 3 4 98 99 _______________ _______________ 200. Complete anger management 1 2 3 4 98 99 _______________ _______________ 201. No contact with victim 1 2 3 4 98 99 _______________ _______________ 202. Attend alcohol safety education school 1 2 3 4 98 99 _______________ _______________ 203. Attend 1 victim impact panel 1 2 3 4 98 99 _______________ _______________ 204. DL s uspended/revoked 1 2 3 4 98 99 _______________ _______________ 205. Abide with order of impoundment 1 2 3 4 98 99 _______________ _______________ 206. Abide by curfew 1 2 3 4 98 99 _______________ _______________ 207. other (specify___________) 1 2 3 4 98 99 _______________ _______________ 208. other (specify___________) 1 2 3 4 98 99 _______________ _______________ 209. other (specify___________) 1 2 3 4 98 99 _______________ _______________ 210. other (specify___________) 1 2 3 4 98 99 _____________ __ _______________ 211. other (specify___________) 1 2 3 4 98 99 _______________ _______________ Turn off tape recorder once column a and column b are completed. [Read] The next set of questions asks you about your perception about the likelihood that y ou will be able to complete or follow the probation condition. The response options are not difficult, relatively easy, about 50/50, somewhat difficult and very difficult (Hand participant yellow answer card) (Read all the conditions and circle the answer option the participant selected, next turn tape recorder on and read column a and column b) (for all conditions circle one and then complete columns a and b with tape recorder on) Not difficult Relatively easy About 50/50 Somewhat difficult Very diffic ult DK RF a. Why do you feel __ is very difficult? ( ask for each coded 5) b. Why do you feel ___ is not difficult? ( ask for coded 1) 212. Commit no new law violation 1 2 3 4 5 98 99 __________ __________ 213. Report to probation once a month 1 2 3 4 5 98 99 __________ __________

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190 (for all conditions circle one and then complete columns a and b with tape recorder on) Not difficult Relatively easy About 50/50 Somewhat difficult Very difficult DK RF a. Why do you feel __ is very difficult? ( ask for each coded 5) b. Why do you feel ___ is not difficult? ( ask for coded 1) 214. Answer truthfully to inquiries by PO 1 2 3 4 5 98 99 __________ __________ 215. Notify PO of changes in residence 1 2 3 4 5 98 99 __________ __________ 216. Notify PO of changes in employment/education 1 2 3 4 5 98 99 __________ __________ 217. Try to obtain employment 1 2 3 4 5 98 99 __________ __________ 218. Maintain employment/school enrollment 1 2 3 4 5 98 99 __________ __________ 219. Allow PO to visit residence 1 2 3 4 5 98 99 __________ __________ 220. Allow PO to visit employment site 1 2 3 4 5 98 99 __________ __________ 221. Pay monthly cost of supervision 1 2 3 4 5 98 99 __________ __________ 222. Pay court costs 1 2 3 4 5 98 99 __________ __________ 223. Com plete CS hours in lieu of fees 1 2 3 4 5 98 99 __________ __________ 224. Complete mandatory CS hours 1 2 3 4 5 98 99 __________ __________ 225. Complete work crew days 1 2 3 4 5 98 99 __________ __________ 226. Complete a jail sentence 1 2 3 4 5 98 99 __________ __________ 227. Pay restitution 1 2 3 4 5 98 99 __________ __________ 228. Submit to random screens 1 2 3 4 5 98 99 __________ __________ 229. Do not possess or consume alcohol 1 2 3 4 5 98 99 __________ __________ 230. Do not possess or consume illegal drugs 1 2 3 4 5 98 99 __________ __________ 231. Participate in alcohol treatment 1 2 3 4 5 98 99 __________ __________

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191 (for all conditions circle one and then complete columns a and b with tape recorder on) Not difficult Relatively eas y About 50/50 Somewhat difficult Very difficult DK RF a. Why do you feel __ is very difficult? (ask for each coded 5) b. Why do you feel ___ is not difficult? (ask for coded 1) 232. Participate in drug treatment 1 2 3 4 5 98 99 __________ __________ 233. Participate in mental health treatment 1 2 3 4 5 98 99 __________ __________ 234. Participate in employment program 1 2 3 4 5 98 99 __________ __________ 235. Complete Milepost class 1 2 3 4 5 98 99 __________ __________ 236. Complete DART program 1 2 3 4 5 98 99 __________ __________ Intervention 1 2 3 4 5 98 99 __________ __________ 238. Complete anger management 1 2 3 4 5 98 99 __________ __________ 239. No contact with victim 1 2 3 4 5 98 99 __________ __________ 240 Attend alcohol safety education school 1 2 3 4 5 98 99 __________ __________ 241. Attend 1 victim impact panel 1 2 3 4 5 98 99 __________ __________ 242. DL suspended/revoked 1 2 3 4 5 98 99 __________ __________ 243. Abide with order of impoundment 1 2 3 4 5 98 99 __________ __________ 244. Abide by curfew 1 2 3 4 5 98 99 __________ __________ 245. other (specify __________) 1 2 3 4 5 98 99 __________ __________ 246. other (specify __________) 1 2 3 4 5 98 99 __________ __________ 247. other (spec ify __________) 1 2 3 4 5 98 99 __________ __________ 248. other (specify __________) 1 2 3 4 5 98 99 __________ __________ 249. other (specify __________) 1 2 3 4 5 98 99 __________ __________ 250. other (specify___________) 1 2 3 4 5 98 99 __________ __________ (Adapted Petersilia & Deschenes 1994b) [Read] 251. What you think about the difficulty of your sentence of probation? (circle one and complete column a) Not difficult 1 Relatively easy 2 About 50/50 3 Somewhat difficult 4 Very difficult 5 DK 98 RF 99 a. Why you feel this way? Please explain _________________

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192 252. [Read] What do you think are some possible obstacles that you will face or are facing that could prevent you from successfully completing or adhering to your conditions of probation? Turn tape recorder off. [Read] Now I am going to ask you some things that possibly could be an obstacle for a person on probation. Please indicate your level of agreement on whether the following items are obstacles for you Your response options are s trongly disagree, disagree, agree and strongly agree. (Hand participant green card) (circle one) Strongly Disagree Disagree Agree Strongly Agree DK RF 253. Finding a job 1 2 3 4 98 99 254. Finding a good paying job 1 2 3 4 98 99 255. Maintaining a job 1 2 3 4 98 99 256. Finding time to report monthly 1 2 3 4 98 99 257. Finding time to do CS hours 1 2 3 4 98 99 258. Finding time to do work crew 1 2 3 4 98 99 259. Transportation to work 1 2 3 4 98 99 260. Transportation to report monthly to probatio n office 1 2 3 4 98 99 261. Transportation to CS location 1 2 3 4 98 99 262. Transportation to work crew 1 2 3 4 98 99 263. Maintaining a residence 1 2 3 4 98 99 264. Paying court costs 1 2 3 4 98 99 265. Paying monthly cost of supervision 1 2 3 4 98 99 266. Paying restitution 1 2 3 4 98 99 267. Participating in treatment 1 2 3 4 98 99 268. Avoiding drinking alcohol 1 2 3 4 98 99 269. Avoiding using drugs 1 2 3 4 98 99 270. Neighborhood conditions 1 2 3 4 98 99 271. Lack of family support 1 2 3 4 98 99 272. Number of probation conditions 1 2 3 4 98 99 273. Turn tape recorder on. [Read] What are some possible things that would help increase the chances of you completing probation? Do you have any suggestions on how to remove or reduce the numbe r of obstacles that you may face while on probation? Turn tape recorder off.

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193 [Read] I am going to ask about your perceptions about different types of criminal sanctions. First, I am going to ask you to rate th e severity of several sentencing sanctions. If you are not familiar with any of the sanctions, please let me know and I can describe them to you. The response options are not severe, somewhat severe, severe and extremely severe (Hand participant red card) Read all the conditions and circle the answe r option the participant selected, next turn tape recorder on and read column a and column b) (for all sanctions circle one and then complete columns a and b with tape recorder on) Not severe Somewhat severe Severe Extremely severe DK RF a. Why do you fe el _____ is severe? (ask for each one coded 4) b. Why do you feel ____ is not severe? (ask for each one coded 1) 274. $100 fine 1 2 3 4 98 99 ____________ _____________ 275. $1000 fine 1 2 3 4 98 99 ____________ _____________ 276. $5000 fine 1 2 3 4 98 99 ____________ _____________ 277. 1 year regular probation 1 2 3 4 98 99 ____________ _____________ 278. 3 years regular probation 1 2 3 4 98 99 ____________ _____________ 279. 5 years regular probation 1 2 3 4 98 99 ____________ _____________ 280. 1 year intensive supervision probation 1 2 3 4 98 99 ____________ _____________ 281. 3 years intensive supervision probation 1 2 3 4 98 99 ____________ _____________ 282. 5 years intensive supervision probation 1 2 3 4 98 99 ____________ _____________ 283. 3 months in jail 1 2 3 4 98 99 ____________ _____________ 284. 6 months in jail 1 2 3 4 98 99 ____________ _____________ 285. 1 year in jail 1 2 3 4 98 99 ____________ _____________ 286. 1 year in prison 1 2 3 4 98 99 ____________ _____________ 2 87. 3 years in prison 1 2 3 4 98 99 ____________ _____________ 288. 5 years in prison 1 2 3 4 98 99 ____________ _____________ 289. 3 months day reporting 1 2 3 4 98 99 ____________ _____________ 290. 6 months day reporting 1 2 3 4 98 99 ____________ _____________ 291. 1 year day reporting 1 2 3 4 98 99 ____________ _____________ 292. 3 months electronic monitoring 1 2 3 4 98 99 ____________ _____________ 293. 6 months electronic monitoring 1 2 3 4 98 99 ____________ _____________ 294. 1 year el ectronic monitoring 1 2 3 4 98 99 ____________ _____________ 295. 3 months boot camp 1 2 3 4 98 99 ____________ _____________ 296. 6 months boot camp 1 2 3 4 98 99 ____________ _____________ 297. 1 year boot camp 1 2 3 4 98 99 ____________ ____________ (Adapted from Petersilia & Deschenes 1994b)

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194 298. (Hand participant orange card) [Read] Which of the listed conditions do you find to be the MOST severe? Why? 299. [Read] Which of the listed conditions do you find to be the LEAST severe? Why? 300 [Read] If you were able to make policy recommendations regarding the types of criminal sanctions that are used in our criminal justice system, what would you recommend? 301. [Read] Is there anything that I have not asked you about conditions of probati on or sanction severity that you feel I should know? Turn tape recorder off. [Read] Now that I have asked you about probation, I would like to ask you about how personally afraid you are of the following crimes. For each of the following crimes please indicate if you are not afraid, somewhat afraid, afraid, or very afraid. (H and participant purple card) In the past year how personally afraid have you been of: (circle one) Not Afraid Somewhat Afraid Afraid Very Afraid DK RF 302. Being approached by a b eggar or panhandler 1 2 3 4 98 99 303. Having someone break into your home while you are there 1 2 3 4 98 99 304. Being raped or sexually assaulted 1 2 3 4 98 99 305. Being murdered 1 2 3 4 98 99 306. Being attacked by someone with a weapon 1 2 3 4 98 99 307. Having your car stolen 1 2 3 4 98 99 308. Being robbed or mugged on the street 1 2 3 4 98 99 309. Having your property damaged 1 2 3 4 98 99 310. Being threatened by someone 1 2 3 4 98 99 311. Being beaten up by someone 1 2 3 4 98 99 31 2. Being shot at while walking down the street 1 2 3 4 98 99 313. Having your property damaged by graffiti or tagging 1 2 3 4 98 99 314. Having someone break into your home while you are away 1 2 3 4 98 99 315. Having someone commit a home invasion ro bbery against you 1 2 3 4 98 99 316. Being the victim of a drive by or random shooting 1 2 3 4 98 99

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195 (circle one) Not Afraid Somewhat Afraid Afraid Very Afraid DK RF 317. Being physically assaulted or attacked by someone without a weapon 1 2 3 4 98 99 318. Being harassed by someone 1 2 3 4 98 99 319. Being a victim of a car jacking 1 2 3 4 98 99 320. Having your money or property taken from you without force or weapon 1 2 3 4 98 99 321. Having your money or property taken from you with force or wea pon 1 2 3 4 98 99 322. Being around drug use or sales 1 2 3 4 98 99 (Adapted from Ferraro, 1995; Lane, et al. 2005; Lane, 2006; Lane et al. 2005; Lane, et. al. 1997) 323. [Read] Are there any other crimes that you are personally afraid of that are not listed here? 324. Turn tape recorder on. [Read] Which of the crimes are you MOST afraid of crime? Why? 325. [Read] Which of the crimes are you LEAST afraid of? Why? Turn tape recorder off. 326. [Read] Now that you have indicated how pers onally afraid you are, I would like to know if you have been a victim of any of the previously listed crimes in the last year? (Read options & circle one) Yes 1 No (skip to # 328) 0 DK (skip to # 328) 98 RF (skip to # 328) 99 327. Turn tape recorde r on. [Read] Please describe which ones and what happened to you? Turn tape recorder off. 328. [Read] Has your family been a victim of any of the previously listed crimes in the last year? (Read options & circle one) Yes 1 No ( skip to # 330 ) 0 DK (skip to # 330 ) 98 RF (skip to # 330 ) 99 329. Turn tape recorder on. [Read] Please describe which crimes and what happened and to whom? Turn tape recorder off.

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196 330. [Read] In general, are you more, less, or equally afraid for other people living in your home as you are for yourself? (Read options & circle one) More Afraid 1 Less Afraid 2 Equally Afraid 3 DK 98 RF 99 (Lane et al., 1997) [Read] Now I would like you to think about your family members. Of those living in your home, please indicate how person ally afraid you are that each of the following family members will be a victim of a crime ? Please tell us how afraid, somewhat afraid, afraid, or very afraid you are that ( Hand participant purple card) (circle one) Not Afraid Somewhat Afraid Afraid Very Af raid N/A DK RF 331. Your father will be a victim of crime 1 2 3 4 97 98 99 332. Your mother will be a victim of crime 1 2 3 4 97 98 99 333. Your husband will be a victim of crime 1 2 3 4 97 98 99 334. Your wife will be a victim of crime 1 2 3 4 97 98 99 335. Your partner will be a victim of crime 1 2 3 4 97 98 99 336. Your son(s) will be a victim of crime 1 2 3 4 97 98 99 337. Your daughter(s) will be a victim of crime 1 2 3 4 97 98 99 338. Your brother(s) will be a victim of crime 1 2 3 4 9 7 98 99 339. Your sister(s)will be a victim of crime 1 2 3 4 97 98 99 340. Other (please specify) ____________ 1 2 3 4 97 98 99 341. Turn tape recorder on. [Read] Are you more afraid for them than yourself? Why? Turn tape recorder off. [ Read]: You have indicated how personally afraid you are for you and your family of the crimes listed. I would like you to indicate how likely it is that in the next year you will become a victim of the following crimes. Is it not likely, somewhat likely, likely, or v ery likely that you will ( Hand participant pink card) (Read options & circle one) Not Likely Somewhat Likely Likely Very Likely DK RF 342. Be approached by a beggar or panhandler 1 2 3 4 98 99 343. Have someone break into your home while you are there 1 2 3 4 98 99 344. Be raped or sexually assaulted 1 2 3 4 98 99 345. Be murdered 1 2 3 4 98 99 346. Be attacked by someone with a weapon 1 2 3 4 98 99 347. Have your car stolen 1 2 3 4 98 99 348. Be robbed or mugged on the street 1 2 3 4 98 99 349. Have your property damaged 1 2 3 4 98 99 350. Be threatened by someone 1 2 3 4 98 99

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197 (Read options & circle one) Not Likely Somewhat Likely Likely Very Likely DK RF 351. Be beaten up by someone 1 2 3 4 98 99 352. Be shot at while walking down the s treet 1 2 3 4 98 99 353. Have your property damaged by graffiti or tagging 1 2 3 4 98 99 354. Have someone break into your home while you are away 1 2 3 4 98 99 355. Have someone commit a home invasion robbery against you 1 2 3 4 98 99 356. Be the vi ctim of a drive by or random shooting 1 2 3 4 98 99 357. Be physically assaulted or attacked by someone 1 2 3 4 98 99 358. Be harassed by someone 1 2 3 4 98 99 359. Be a victim of a car jacking 1 2 3 4 98 99 360. Have your money or property taken fro m you without force or weapon 1 2 3 4 98 99 361. Have your money or property taken from you with force or weapon 1 2 3 4 98 99 362. Be around drug use or sales 1 2 3 4 98 99 ( Adapted from Ferraro, 1995; Lane, et al. 2005; Lane, 2006; Lane et al. 2005; Lane, et. al. 1997) [Read]: Now I would like to ask you about the crimes that you have committed in the past, please indicate if you have taken part in any of the following crimes by indicating yes or no? Please remember that your answers are confidential (Read options & circle one) Yes No DK RF 1 0 98 99 364. Raped or sexually assaulted someone 1 0 98 99 365. Attacked someone with a weapon 1 0 98 99 366. Stolen a car 1 0 98 99 367. Robbed or mugged someone on the street 1 0 98 99 1 0 98 99 369. Threatened someone with a weapon 1 0 98 99 370. Beaten up or physically assaulted someone 1 0 98 99 371. Shot at someone while walking down the street 1 0 98 99 1 0 98 99 1 0 98 99 374. Committed a home invasion robbery against someone 1 0 98 99 375. Participated in a drive by or random shooting 1 0 98 99 376. Harassed or threatened someone 1 0 98 99 377. Car jacked someone 1 0 98 99

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198 Yes No DK RF 378. Dealt or delivered drugs (made, sold, or moved) 1 0 98 99 379. Possessed drugs (marijuana, cocaine, crack, etc) 1 0 98 99 380. Been in a gang 1 0 9 8 99 1 0 98 99 1 0 98 99 383. Approach someone on the street asking for money or trying to panhandle 1 0 98 99 384. Turn tape recorder on. [Read] D o you feel that taking part in these activities has made you feel more or less afraid? Why? 385. [Read] Do you feel that taking part in these activities has made you feel more or less afraid for your family? Why? Turn tape recorder off. 386. [Read] D o you feel that your participation in crime makes it more or less likely that your family will be (Read options & circle one) Much less likely 1 Less likely 2 More likely 3 Much more likely 4 DK 98 RF 99 [Read]: Now I would like to ask you about some of things you have done to protect yourself from crime. Please remember your answers are confidential and if you prefer not to answer a question you may skip it. In order to feel safer from being a vict im of crime, in the past y Yes No DK RF 387. Buy or secure a gun 1 0 98 99 388. Carry a gun 1 0 98 99 389. Carry a weapon other than a gun when you went out 1 0 98 99 390. Arrange to go out with someone so you would not be alone 1 0 98 99 391. Avoid certain areas of your neighborhood or community 1 0 98 99 392. Join a gang for protection 1 0 98 99 393. Hangout with gang members 1 0 98 99 394. Buy an alarm or security system 1 0 98 99 395. Install extra locks on your home or car 1 0 98 99 396. Buy a watchdog 1 0 98 99 397. Added outside lighting 1 0 98 99 398. Limit or change your daily routine because of crime 1 0 98 99 (Adapted from Lane, 2009; Lane et al., 1997; Lane & Meeker, 2004; Ferraro, 1995)

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199 399. Turn tape recorder on [Read] What crime(s) were you trying to avoid by taking the previously listed options? Please explain. 400. [Read] Do you feel that doing these things has helped keep you safe? Please explain how. 401. [Read] Now we have reached the last section of the questionnaire. Here I would like to ask you about the neighborhood you live in. Please think of your current neighborhood when answering the following questions. How would you describe the people who l ive in your neighborhood in terms of income? How many of them live in poverty? 402. [Read] How would you describe the people who live in your neighborhood in terms of education? 403. [Read] If you had a problem, could you rely on your neighbors for help? (Read options & circle one) Yes 1 No 0 DK 98 RF 99 404. [Read] What, specifically, do you think you could rely on your neighbors for? Why? 405. [Read] What could you not rely on them for? Why? Turn tape recorder off. 406. [Read] Can you trust your neighbors? ( Read options & circle one) (Earls, et. al., 1994) Never 1 Some of the time 2 All of the time 3 DK 98 RF 99 407. [Read] Would your neighbors be willing to help one another? (Read options & circle one) (Sampson & Raudenbush, 2001) Yes 1 No 0 DK 98 RF 99 408. [Read] Would your neighbors do something if they saw unattended kids misbehaving? (Read options & circle one) (Sampson & Raudenbush, 2001) Yes 1 No 0 DK 98 RF 99 409. [Read] Would your neighbors do something if they saw a crime occur? (Read options & circle one ) (Sampson & Raudenbush, 2001) Yes 1 No 0 DK 98 RF 99

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200 410. [Read] How much do you feel like you belong to your (Read options & circle one) (Lane, et al., 1997; Ferraro, 1995) part of it 1 Sometimes I feel a part of i t 2 I feel very much a part of it 3 DK 98 RF 99 411. [Read] Which of the following best illustrates how racially mixed your neighborhood is: (Read options & circle one) Not very mixed: Most people are of the same race 1 Somewhat mixed: Some people of different race 2 Very mixed People are of various racial backgrounds 3 DK 98 RF 99 412. [Read] When thinking of those who live near your home, if you were to move away in the next year, how many would you really miss? (Read options & circle one) (Ferra ro, 1995) None 1 Some of them 2 A lot of them 3 All of the them 4 DK 98 RF 99 413. [Read] How often do people move in and out of your neighborhood? (Read options & circle one) (Sampson & Raudenbush, 2001) Rarely 1 Sometimes 2 Often 3 DK 98 RF 99 41 4. [Read] Do you see strangers in your neighborhood? (Read options & circle one) (Ferraro, 1995) Never 1 Almost never 2 Sometimes 3 Very often 4 DK 98 RF 99 [Read]: The next questions ask about how safe you feel in your neighborhood. Please indicate if you feel very unsafe, somewhat unsafe, somewhat safe, or very safe. ( Hand participant blue card) (Adapted from Ferraro, 1995) (circle one) Very unsafe Somewhat unsafe Somewhat safe Very safe DK RF 415. How safe do you feel walking alone in your neighborh ood during the day 1 2 3 4 98 99 416. How safe do you feel out alone in your neighborhood at night 1 2 3 4 98 99 417. How safe from crime do you feel inside your home during the day 1 2 3 4 98 99 418. How safe from crime do you feel inside your home du ring the night 1 2 3 4 98 99 419. How safe do you feel living in your neighborhood? 1 2 3 4 98 99 420. [Read] Is there any area in your neighborhood where you would be afraid to walk alone at night? (Read options & circle one) Yes 1 No 0 DK 98 RF 99 421. [Read] Is there any area in your neighborhood where you would be afraid to walk alone at during the day? (Read options & circle one) Yes 1 No 0 DK 98 RF 99 422. [Read] In the past year, do you feel safer, not as safe, or about the same in your co mmunity? (Read options & circle one) (Lane et al., 1997) Safer 1 Not as safe 2 About the same 3 DK 98 RF 99

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201 [Read]: Based on the following crimes listed, do you feel that your community has a lot, moderate amount, small amount, or none of the following c rimes? (Hand participant light blue card) (circle one) None Small Amount Moderate Amount A lot DK RF 423. Property crime like burglary or theft 1 2 3 4 98 99 424. Violent crime like assault or murder 1 2 3 4 98 99 425. Drug related crimes (selling or di stributing) 1 2 3 4 98 99 426. Property crimes by gangs 1 2 3 4 98 99 427. Violent crimes by gangs 1 2 3 4 98 99 (Adapted from Lane et al., 1997) [Read] I am going to ask you some questions about the neighborhood you live in, as you define it. I would like you to think of your neighborhood and some of the problems in your community and how serious they are. Please indicate if the following items are a big problem, somewhat of a problem, problem, or not a problem. ( Hand participant light purple card) ( circle one) Not a problem Somewhat of a problem A problem A big problem DK RF 428. Litter, broken glass, or trash on sidewalks or streets 1 2 3 4 98 99 429. Graffiti on buildings or walls 1 2 3 4 98 99 430. Vacant or deserted homes, cars, or storefronts 1 2 3 4 98 99 431. Buildings that are falling apart or run down 1 2 3 4 98 99 432. Drinking in public 1 2 3 4 98 99 433. People selling drugs on the streets 1 2 3 4 98 99 434. Groups of teens or adults hanging out and causing trouble 1 2 3 4 98 99 4 35. Poverty or financial hardship 1 2 3 4 98 99 436. Language differences between residents 1 2 3 4 98 99 437. Cultural differences between residents 1 2 3 4 98 99 438. Too many people living in one home 1 2 3 4 98 99 439. Gunfire 1 2 3 4 98 99 440. G angs 1 2 3 4 98 99 441. People drunk on the streets 1 2 3 4 98 99 442. Unsupervised youth 1 2 3 4 98 99 443. Kids behaving badly 1 2 3 4 98 99 444. People moving in and out a lot 1 2 3 4 98 99 445. Needles on the street 1 2 3 4 98 99 446. People using drugs 1 2 3 4 98 99 1 2 3 4 98 99

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202 (Adapted from Earls, et. al. 1994 95; Lane, et. al. 1997; Ferraro, 1995; Sampson & Raudenbush, 2001 ). 448. Turn tape recorder on. [Read] Specifically, w hat crimes are MOST problematic to you in your neighborhood? Why? 449. [Read] What crimes are LEAST problematic to you in your neighborhood? Why? Turn tape recorder off. 450. [Read] Overall, in the past year, would you say your community has become a better place to live, has gotten worse, or is about the same as it used to be? (Read options & circle one) (Lane, et al., 1997) Worse 1 Better 2 About the same 3 DK 98 RF 99 451. [Read] Do you think that crime in your neighborhood has increased, re mained the same, or decreased in the last year? (Read options & circle one) (Lane, et al., 1997) Increased 1 Stayed the same 2 Decreased 3 DK 98 RF 99 452. Turn tape recorder on. [Read] If you have noticed an increase in crime, which crimes would you i ndicate to have increased? 453. [Read] Is there anything about fear of crime that you feel is important for me to know that I have not asked you about? Turn tape recorder off and thank th e participant for participating.

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203 APPENDIX I OFFENSE CATEGORI ES USED BY ALACHUA C OUN T Y PROBATION Table I 1. Alachua County Court Services Probation Offense Category by Type of Offenses Type of Offense Code # Offenses (also used for VOPs D 1 Possession or use of drug paraphernalia D 2 Possession or use of na rcotic equipment D 3 Possession of marijuana not more than 20 grams D 35 Cocaine possession D 46 Marijuana with intent to sell D 51 Dangerous drugs: Keep shop or vehicle for drugs D 56 Sale of control substance D 57 Possession of control substance P 11 Criminal Mischief over 200 Dollars under 1000 dollars P 12 Larceny: Petit first degree property 100 to under 300 P 13 Retail theft P 15 Trespass P 19 Hit and Run: Leaving a scene of an accident P 20 Fraud: Illegal use of CC P 40 Burglary P 4 1 Conservation animal: Torment, mutilation, kill P 47 Grand theft P 58 Larceny of credit card P 62 Attempt to commit burglary P 64 Fraud: Obtain merchant money with false receipt PO 4 Alcohol possession under 21 PO 5 DUI PO 6 No motor vehicle regist ration/ attached not assigned PO 7 Obstruction of justice Harass PO 8 Reckless Driving PO 9 Driving while license suspended or revoked PO 10 No Valid Drivers license PO 14 Worthless check PO 16 Resisting or obstruct officer without violence PO 21 Violation of domestic injunction PO 22 Make false report PO 23 Improper exhibit of firearm or dangerous weapon PO 25 Contempt of court PO 27 False ID to LEO PO 28 Contribute delinquency of minor: Parent fail to require school PO 29 Disorderly i ntoxication PO 31 Resist recovery of property PO 32 Expired DL PO 33 Open container PO 34 Conditional release violation: Pretrial release PO 36 Disorderly conduct PO 42 Child neglect PO 43 Refuse to submit to DUI test PO 44 Contributing to delinq uency of minor PO 45 Refuse to accept/sign citation PO 48 Obstruction of justice: threaten

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204 Table I 1 (continued). Alachua County Court Services Probation Offense Category by Type of Offenses Type of Offense Code # Offenses (also used for VOPs PO 50 Out of county warrant PO 52 DWLS Habitual PO 53 Flee/elude PO 54 Forgery of DL with altered PO 55 Misuse 911 PO 63 Operate vehicle DL restriction PO 66 Failure to appear PO 67 Resist with violence V 17 Battery: touch or strike V 18 Domestic Batt ery: Touch or Strike V 24 Aggravated battery: Cruelty toward child V 26 Assault V 30 Felony Battery V 37 Aggravated battery with weapon V 38 Aggravated battery V 39 Dating violence V 49 Aggravated assault V 59 Domestic assault V 60 Sex offense unnatural and lascivious act V 61 Domestic stalking V 65 Aggravated battery on pregnant victim V 68 Battery on LEO/FF/EMT

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205 LIST OF REFERENCES Berg, B. (2009). Qualitative research methods for the social sciences. Boston, MA: Pearson. Berg, K., & Lati n, R. (2008). Essentials of research methods in health, physical education, exercise science and recreation. Philadelphia, PA: Lippincot, Williams & Wilkins. Bursik, R. (1984). Urban dynamics and ecological studies of delinquency. Social Forces, 63(2), 39 3 413. Bursik, R. & Grasmick, H. (1993). The use of multiple indicators to estimate crime Conklin, J. (1975). The impact of crime. New York: Macmillan. Covington, J. & Taylor, R. (1991). Fear of crime in u rban residential neighborhoods: Imp lications of Between and Within neighborhood sources for current models. The Sociological Quarterly, 32(2), 231 249. DuBow, F., McCabe, E., & Kaplan,G. (1979). Reactions to crime: A critical review of the literature. Washington, D.C.: National Institute of Law Enforcem ent and Criminal Justice, Government Printing Office. Dull, R. & Wint, A. (1997). Criminal Victimization and its effect on fear of crime and justice attitudes. Journal of Interpersonal Violence, 12(5): 748 758. Ferraro & LaGrange (1987). The measurement o f fear of crime. Sociological Inquiry, 57, 70 101. Ferraro, K. (1995). Fear of Crime: Interpreting victimization risk. State University of New York Press, Albany, NY. Social For ces, 75(2): 667 690. Ferraro, K. & Lagrange, R. (1992) Are older people most afraid of crime? Reconsidering age differences in fear of victimization. Journal of Gerontology, 47(5), 233 244. me related fea rs on campus: Are fear provoking cues gendered? Journal of Contemporary Criminal Justice, 25:300 321. Garofalo, J. (1981). The fear of crime: Causes and consequences. The Journal of Criminal Law & Criminology. 72(2), 839 857. Gates, L. & Rohe, W. (1987). Fear and reactions to crime: A revised model. Urban Affairs Quarterly, 22(30: 425 453.

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211 BIOGRAPHICAL SKETCH Katheryn Zambrana earned her Bachelor of Arts in criminology and political s cience from the University of Florida in 2009. She wi ll earn her Ma ster of Arts in 2012 in criminology, l aw and society at the University of Florida as well; where she hopes to continue on to pursue her PhD.