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Fiscal Equity and the Effects of Changes in Demographics on Performance Funding in the Florida Community College System,...

Permanent Link: http://ufdc.ufl.edu/UFE0021870/00001

Material Information

Title: Fiscal Equity and the Effects of Changes in Demographics on Performance Funding in the Florida Community College System, 2002-2006
Physical Description: 1 online resource (191 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: demographics, equity, fiscal, funding, gini, horizontal, lorenz, perfomance, spellings, state, vertical
Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: With higher education costs rising faster than the Consumer Price Index, policymakers are concerned that costs will affect access to education. They are concerned that federal and state support may be unable to keep pace with rising costs. Parents and students are concerned about rising student fees. Higher education administrators are concerned about funding equity and quality of education. The Spellings Commission Report of 2006 focused national attention on changing demographics and the need for higher education to educate citizens more effectively, especially minorities and other special populations. The Commission Report states that as higher earning, highly educated baby boomers reach retirement age, the workforce needed for continued U.S economic growth will require minorities and other populations to backfill high-skill positions being vacated by baby boomers. Currently, these special populations are least educated, lower earners, and smaller per capital tax payers. This issue is of grave concern. Previous research studies in the State of Florida found declining equity in community college per-student FTE revenue distributions when performance funding is included. Only one of the previous findings was significant at the confidence level of 95%. This 2007 research study addresses questions of horizontal fiscal equal with performance funding included, excluded, and indexed to special population demographics in college service areas. This study found the following: (a) evidence of improving equity in 2005-06 owing to funding formula-driven equalization enhancements implemented that year, (b) overall declining equity for three of the equity statistic tests significant at the 95% confidence level when performance funding is included, and (c) that performance funding indexed to special populations in college service areas is not a complete solution to funding equity, but may warrant further research. The study also contributes to horizontal fiscal equity theory by shedding new light on the effects of calculating the Gini coefficient equity statistic with weighted full-time-equivalent student enrollment.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Campbell, Dale F.
Local: Co-adviser: Tyree, Lawrence W.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021870:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021870/00001

Material Information

Title: Fiscal Equity and the Effects of Changes in Demographics on Performance Funding in the Florida Community College System, 2002-2006
Physical Description: 1 online resource (191 p.)
Language: english
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2008

Subjects

Subjects / Keywords: demographics, equity, fiscal, funding, gini, horizontal, lorenz, perfomance, spellings, state, vertical
Educational Administration and Policy -- Dissertations, Academic -- UF
Genre: Higher Education Administration thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: With higher education costs rising faster than the Consumer Price Index, policymakers are concerned that costs will affect access to education. They are concerned that federal and state support may be unable to keep pace with rising costs. Parents and students are concerned about rising student fees. Higher education administrators are concerned about funding equity and quality of education. The Spellings Commission Report of 2006 focused national attention on changing demographics and the need for higher education to educate citizens more effectively, especially minorities and other special populations. The Commission Report states that as higher earning, highly educated baby boomers reach retirement age, the workforce needed for continued U.S economic growth will require minorities and other populations to backfill high-skill positions being vacated by baby boomers. Currently, these special populations are least educated, lower earners, and smaller per capital tax payers. This issue is of grave concern. Previous research studies in the State of Florida found declining equity in community college per-student FTE revenue distributions when performance funding is included. Only one of the previous findings was significant at the confidence level of 95%. This 2007 research study addresses questions of horizontal fiscal equal with performance funding included, excluded, and indexed to special population demographics in college service areas. This study found the following: (a) evidence of improving equity in 2005-06 owing to funding formula-driven equalization enhancements implemented that year, (b) overall declining equity for three of the equity statistic tests significant at the 95% confidence level when performance funding is included, and (c) that performance funding indexed to special populations in college service areas is not a complete solution to funding equity, but may warrant further research. The study also contributes to horizontal fiscal equity theory by shedding new light on the effects of calculating the Gini coefficient equity statistic with weighted full-time-equivalent student enrollment.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis: Thesis (Ph.D.)--University of Florida, 2008.
Local: Adviser: Campbell, Dale F.
Local: Co-adviser: Tyree, Lawrence W.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2010-05-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2008
System ID: UFE0021870:00001


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1 FISCAL EQUITY AND THE EFFECTS OF CHANGES IN DEMOGRAPHICS ON PERFORMANCE FUNDING IN THE FLOR IDA COMMUNITY COLLEGE SYSTEM, 2002-2006 By CONFERLETE CARNEY A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2008

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2 2008 Conferlete Carney

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3 To my wife, Angela, thank you for marrying me and being my friend. To my children Kim and Donald, and grand children Daysha, Donald Jr., DaVonna, Dante, and Jayden. I pray for each of you every day. You, too, can do this work and more

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4 ACKNOWLEDGMENTS I wish to acknowledge Dr. Dale F. Ca mpbell, my dissertation chair, for his leadership, guidance, and encouragement through the doctoral program. I thank Dr. Campbell also for the many opportunities to network with nati onal leaders in higher education. I also acknowledge and thank drs. Davi d Honeyman, Lawrence W. Tyree, and Lynn Leverty for serving on the committee. I especial ly thank drs. Tyree for timely mentoring, Honeyman for his literary work in horizontal fi scal equity, and Levert y, for the opportunity to learn the meaning and importance of integrity in public administration. Finally, I acknowledge and thank Dr. Gary Ya ncey, Ms. Patti Adkins and Messrs. Chuck Prince and Edward Cisek of the Florida Department of Education for oppor tunities to learn about the Florida Community College System Funding Model as well as funding policy formation.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........8 LIST OF FIGURES.......................................................................................................................12 ABSTRACT...................................................................................................................................15 CHAPTER 1 INTRODUCTION..................................................................................................................17 The Spellings Commission Report......................................................................................... 17 The Importance of Higher Education..................................................................................... 18 Concerns About Education Quality and Costs.......................................................................19 Shifts in Higher Education Funding.......................................................................................20 Rising Student Tuition Costs.................................................................................................. 21 Rapid Changes in American Demographics........................................................................... 22 Performance Based Funding...................................................................................................22 The Concept of Equity.......................................................................................................... ..23 Previous Equity Research Findings........................................................................................25 Purposes of the Study.............................................................................................................26 Research Questions............................................................................................................. ....26 Significance of the Study........................................................................................................27 Definition of Terms................................................................................................................28 Limitations.................................................................................................................... ..........30 2 REVIEW OF RELATED LITERATURE.............................................................................. 32 The Changing Demographics of America..............................................................................32 Florida Demographics........................................................................................................... .35 Accountability in Higher Education.......................................................................................37 The Concept of Performance in Higher Education................................................................. 42 Performance Budgeting, Funding, and Reporting In Higher Education ................................ 43 Performance Measures in Higher Education.......................................................................... 45 Performance Funding in Florida Higher Education................................................................ 48 Performance Measures and Indicators in Florida Community Colleges................................ 50 The Concept of Equity in Higher Education.......................................................................... 53 Statistics for Measuring E quity in Public Schools................................................................. 55 Range...............................................................................................................................57 Restricted Range..............................................................................................................58 Federal Range Ratio........................................................................................................ 59 Coefficient of Variation................................................................................................... 60 McLoone Index...............................................................................................................61

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6 Gini Coefficient and Lorenz Curve.................................................................................62 Weighted Versus Unweighted Dispersion Measures............................................................. 63 Fiscal Equity in Florida Community Colleges....................................................................... 65 Summary.................................................................................................................................68 3 RESEARCH METHODOLOGY........................................................................................... 70 Purposes of the Study.............................................................................................................70 Research Problem...................................................................................................................71 Research Questions............................................................................................................. ....71 Research Design.....................................................................................................................72 Population of the Study..........................................................................................................72 Data Analysis..........................................................................................................................73 Range...............................................................................................................................74 Restricted Range..............................................................................................................74 Federal Range Ratio........................................................................................................ 75 Coefficient of Variation................................................................................................... 75 McLoone Index...............................................................................................................76 Gini Coefficient and Lorenz Curve.................................................................................77 Summary.................................................................................................................................78 4 DATA ANALYSIS AND RESULTS.................................................................................... 82 Raw Data, Data Calculations, Statistics Measures................................................................. 82 Research Question One.......................................................................................................... .83 Range Performance Included........................................................................................ 83 Range Performance Excluded....................................................................................... 84 Restricted Range Performance Included....................................................................... 85 Restricted Range Performance Excluded...................................................................... 86 Federal Range Ratio Performance Included................................................................. 87 Federal Range Ratio Performance Excluded................................................................ 88 Coefficient of Variation Performa nce Included............................................................ 89 Coefficient of Variation Performa nce Excluded........................................................... 90 McLoone Index Performance Included......................................................................... 90 McLoone Index Performance Excluded........................................................................ 91 Gini Coefficient Performance Included........................................................................ 92 Gini Coefficient Performance Incl uded: ProgramCost-Weighted FTE....................... 92 Gini Coefficient Performance Excl uded: Program-Cost W eighted FTE...................... 93 Gini Coefficient Performance Include d: Non-Program-Cost Weighted FTE ............... 94 Gini Coefficient Performance Exclude d: Non-Program-Cost W eighted FTE.............. 95 Research Question Two.......................................................................................................... 95 Range With Special Population Demogra phics Adjusted Performa nce Included........ 96 Restricted Range With Special Population Demographics Adjusted Perform ance Included........................................................................................................................97 Federal Range Ratio With Special Population Dem ographics Adjusted Performance Included.................................................................................................. 98

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7 Coefficient of Variation With Speci al Population Dem ographics Adjusted Performance Included.................................................................................................. 99 McLoone Index With Special Populati on Demographics Adjusted Perform ance Included......................................................................................................................100 Gini Coefficient With Special Popula tion Demographics Adjusted Perform ance Included: Program-Cost Weighted FTE.................................................................... 100 Gini Coefficient With Special Popula tion Demographics Adjusted Perform ance Included (Non-Program-Cost Weighted)................................................................... 101 Bivariate Correlation Analysis: Befo re and After SPDA Performa nce........................102 Lorenz Curve........................................................................................................................103 Lorenz Curves With and Without Pe rforma nce Funds Program Cost-Weighted...... 104 Lorenz Curves With and Without Performa nce Funds Non-Program CostWeighted....................................................................................................................104 Lorenz Curves With SPDA Adjusted and NonSPDA-Adjusted-Performance Funds Non-Program Cost-W eighted.......................................................................... 104 Summary...............................................................................................................................105 5 DISCUSSION, OBSERVAT IONS, CONCLUSIONS........................................................ 156 Discussion of Results and Observations............................................................................... 156 Research Question One Performa nce Included..........................................................156 Research Question One Performance Excluded......................................................... 158 Research Question Two SPDA-Performance Included............................................... 161 Effects of Capacity Restoration Funding Policy............................................................... 164 Effects of Compression / Equalization Funding Policy.................................................... 165 Areas for Further Research................................................................................................... 166 Implications for Policymakers and College Administrators................................................. 167 Implications for Horizontal Equity Theory.......................................................................... 168 Researchers Perspective......................................................................................................169 APPENDIX RAW DATA: STATE SUPPORT FU NDING 2001-02 THROUGH 2005-06..... 174 LIST OF REFERENCES.............................................................................................................183 BIOGRAPHICAL SKETCH.......................................................................................................191

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8 LIST OF TABLES Table page 2-1 Summary of previous research findings Brown (1999) and Yancey (2002)..................... 69 3-1 Florida counties by commun ity college serving areas....................................................... 79 3-2 College-age black males in the community college service areas for years 2002, 2003, 2004, 2005, and 2006............................................................................................... 80 3-3 College-age male and female Hispanics in the community colle ge service areas for years 2002, 2003, 2004, 2005, and 2006. .......................................................................... 81 4-1 Descriptive statistics for range, coeffi cient of variation, McLoone index and Gini coefficient for operating funds per FTE for Florida community colleges with performa nce funds included.............................................................................................106 4-2 Descriptive statistics for restricted ra nge and federal range ratio for operating funds per FTE for Florida community colleges with perform ance funds included...................106 4-3 Descriptive statistics for range, coeffi cient of variation, McLoone index and Gini coefficient for operating funds per FTE for Florida community colleges with performa nce funds excluded............................................................................................ 107 4-4 Descriptive statistics for restricted ra nge and federal range ratio for operating funds per FTE for Florida community colleg es with perform ance funds excluded.................. 107 4-5 Descriptive statistics for range, coeffi cient of variation, McLoone index and Gini coefficient for non-programcost-weighted operating funds per FTE for Florida community colleges with performance funds included................................................... 108 4-6 Descriptive statistics for range, coeffi cient of variation, McLoone index and Gini coefficient for non-programcost-weighted operating funds per FTE for Florida community colleges with performance funds excluded................................................... 108 4-7 Range for operating funds per FTE for Florida community colleges with performa nce funds included.............................................................................................109 4-8 Range for operating funds per FTE for Florida community colleges with performa nce funds excluded............................................................................................ 110 4-9 Restricted range for opera ting funds per FTE for Florid a community colleges with performa nce funds included.............................................................................................111 4-10 Restricted range for opera ting funds per FTE for Florid a community colleges with performa nce funds excluded............................................................................................ 112

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9 4-11 Federal range ratio for operating funds per FTE for Florida community colleges with perform ance funds included.............................................................................................113 4-12 Federal range ratio for operating funds per FTE for Florida community colleges with perform ance funds excluded............................................................................................ 114 4-13 Coefficient of variation for operating funds per FTE for Florida community colleges with perform ance funds included..................................................................................... 115 4-14 Coefficient of variation for operating funds per FTE for Florida community colleges with perform ance funds excluded.................................................................................... 116 4-15 McLoone index for operating funds per FTE for Florida community colleges with performa nce funds included.............................................................................................117 4-16 McLoone index for operating funds per FTE for Florida community colleges with performa nce funds excluded............................................................................................ 118 4-17 Gini Coefficient for Operating Funds pe r FTE for Florida Community Colleges With Perform ance Funds Included...........................................................................................119 4-18 Gini coefficient for operating funds for Florida community colleges with performa nce funds excluded............................................................................................ 120 4-20 Gini coefficient for operating funds per non-programcost-weighted FTE for Florida community colleges with performance funds excluded................................................... 122 4-21 Descriptive statistics for range, coeffi cient of variation, McLoone index and Gini coefficient for operating funds per FTE for Florida community colleges with program-cost-weighted special population dem ographics adjustment performance funds included..................................................................................................................123 4-22 Descriptive statistics for restricted ra nge and federal range ratio for operating funds per FTE for Florida community colleges with prog ram-cost-weighted special population demographics adjustment performance funds included................................. 123 4-23 Descriptive statistics for Gini coefficient for operating funds per FTE for Florida community colleges with non-program -cost-weighted special population demographics adjustm ent performance funds included...................................................124 4-24 Range for operating funds per FTE for Florida community co lleges with special population dem ographics adjustment inde x performance funds included for years 2001-02 through 2005-06................................................................................................125 4-25 Restricted range for opera ting funds per FTE for Florid a community colleges with special population demo graphics adjustment index performance funds included for years 2001-02 through 2005-06.......................................................................................126

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10 4-26 Federal range ratio for operating funds per FTE for Florida community colleges with special population dem ographics adjustment index performance funds included for years 2001-02 through 2005-06.......................................................................................127 4-27 Coefficient of variation for operating funds per FTE for Florida community colleges with special population dem ographics adju stment index performance funds included for years 2001-02 through 2005-06.................................................................................128 4-28 McLoone index for operating funds per FTE for Florida community colleges with special population demo graphics adjustment index performance funds included for years 2001-02 through 2005-06.......................................................................................129 4-29 Gini coefficient for operating funds pe r FTE for Florida community colleges with special population demo graphics adjustment index performance funds included for years 2001-02 through 2005-06.......................................................................................130 4-30 Gini coefficient for operating funds per non-programcost-weighted FTE for Florida community colleges with special populati on demographics index performance funds included for years 2001-02 through 2005-06................................................................... 131 4-31 Spearmans rho correlation statistics for Measure II before and after for s pecial population demographic adjustment index performance funds....................................... 132 4-32 Weighted black male and ESL/ENS de gree comp leters for Florida community colleges for years 2000-01, 2001-02, 2002-03, 2003-04 for performance fund distributions in years 20 02, 2003, 2004, 2005, 2006, respectively.................................. 133 4-33 Special population demographics adjustme nt indexes by Florida community college for years 2002, 2003, 2004, 2005, and 2006....................................................................134 4-34 Measure II performance fund distributi ons before and after special population demographics adjustm ents by Florida community college for years 2002, 2003 and 2004. 135 4-35 Measure II performance fund distributi ons before and after special population demographics adjustm ents by Florida co mmunity college for years 2005 and 2006...... 136 4-36 Measure II performance and total perfo rm ance fund distributions after special population demographics adjustments by Fl orida community college for years 2002, 2003 and 2004..................................................................................................................137 4-37 Measure II performance and total perfo rm ance fund distributions after special population demographics adjustments by Fl orida community college for years 2005 and 2006...........................................................................................................................138 5-1 ANOVA regression of per-s tudent FTE revenue equity with performa nce funds included for Florida community coll eges years 2001-02 through 2005-06.....................170

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11 5-2 Florida community colleges in lower quart ile of per-student FTE revenue equity with weighted performa nce funds includ ed for years 2001-02 through 2005-06....................170 5-3 Florida community colleges in lower quart ile of per-student FTE revenue equity with non-weighted performa nce funds in cluded for years 2001-02 through 2005-06............ 170 5-4 ANOVA regression of per-s tudent FTE revenue equity with performa nce funds excluded for Florida community coll eges years 2001-02 through 2005-06....................171 5-5 Florida community colleges in lower quart ile of per-student FTE revenue equity with weighted performa nce funds excl uded for years 2001-02 through 2005-06................... 171 5-6 Florida community colleges in lower quart ile of per-student FTE revenue equity with non-weighted performa nce funds excl uded for years 2001-02 through 2005-06............ 171 5-7 ANOVA regression of per-s tudent FTE revenue equity with special population demographics adjusted perform ance Funds included for Florida community colleges years 2001-02 through 2005-06.......................................................................................172 5-8 Florida community colleges in lower quart ile of per-student FTE revenue equity with weighted special population demographics adjusted perform ance funds included for years 2001-02 through 2005-06.......................................................................................172 5-9 Florida community colleges in lower quart ile of per-student FTE revenue equity with non-weighted special population demographi cs adjusted perform ance funds included for years 2001-02 through 2005-06.................................................................................172 5-10 Florida community colleges percenta ges of performa nce based budget funds and Measure II special population funds to to tal funds available for years 2001-02 through 2005-06...............................................................................................................173 5-11 FTE growth compared to growth in to tal funds available to Fl orida community colleges For Years 2001-02 through 2005-06................................................................. 173

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12 LIST OF FIGURES Figure page 4-1 Range and predicted range for operating funds per FTE with performance funds included....................................................................................................................... .....109 4-2 Range and predicted range for operating funds per FTE with performance fund excluded....................................................................................................................... ....110 4-3 Restricted range for opera ting funds per FTE for Florid a community colleges with performa nce funds included.............................................................................................111 4-5 Federal range ratio for operating funds per FTE for Florida community colleges with perform ance funds included.............................................................................................113 4-9 McLoone index for operating funds per FTE for Florida community colleges with performa nce funds included.............................................................................................117 4-10 McLoone index for operating funds per FTE for Florida community colleges with performa nce funds excluded............................................................................................ 118 4-11 Gini coefficient for operating funds pe r FTE for Florida community colleges with performa nce funds included.............................................................................................119 4-12 Gini coefficient for operating funds pe r FTE for Florida community colleges with performa nce funds excluded............................................................................................ 120 4-13 Gini coefficient for non-program-cost-weig hted operating funds per FTE for Florida community colleges with non-SPDA-adjust ed performa nce funds included.................. 121 4-14 Gini coefficient for non-program-cost-weig hted operating funds per FTE for Florida community colleges with performa nce funds excluded................................................... 122 4-15 Range for operating funds per FTE for Florida community co lleges with special population dem ographics adjustment index performance funds included....................... 125 4-16 Restricted range for opera ting funds per FTE for Florid a community colleges with special population demo graphics adjustment index Performance funds included for years 2001-02 through 2005-06.......................................................................................126 4-17 Federal range ratio for operating funds per FTE for Florida community colleges with special population dem ographics adjustment index performance funds included for years 2001-02 through 2005-06.......................................................................................127 4-18 Coefficient of variation for operating funds per FTE for Florida community colleges with special population dem ographi cs adjustment index performanc e funds included for years 2001-02 through 2005-06.................................................................................128

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13 4-19 McLoone index for operating funds per FTE for Florida community colleges with special population demo graphics adjustment index performance funds included for years 2001-02 through 2005-06.......................................................................................129 4-20 Gini coefficient for operating funds pe r FTE for Florida community colleges with special population demo graphics adjustment index performance funds included for years 2001-02 through 2005-06.......................................................................................130 4-21 Gini coefficient for non-program-cost-weig hted operating funds per FTE for Florida community colleges with special populat ion demographics adjustme nt index performance funds included for years 2001-02 through 2005-06................................... 131 4-22 Descriptive statistics frequency histogram for blac k males and Hispanics in respective college servic e areas for year 2001-02........................................................... 139 4-23 One-way ANOVA mean plot for black males and Hispanics in respective college service areas for year 2001-02......................................................................................... 139 4-24 Descriptive statistics frequency histogram for blac k males and Hispanics in respective college servic e areas for year 2005-06........................................................... 140 4-25 One-way ANOVA mean plot for black males and Hispanics in respective college service areas for year 2005-06......................................................................................... 140 4-26 Lorenz curve 2001-2002 for Florida community colleges with program-costweighted operating funds with and without perform ance funds included....................... 141 4-27 Lorenz curve 2002-2003 for Florida co mmunity colleges with program-costweighted operating funds per FTE with and without performance funds included. ........142 4-28 Lorenz curve 2003-2004 for Florida community colleges with program-costweighted operating funds per FTE with and without performance funds included. ........143 4-29 Lorenz curve 2004-2005 for Florida co mmunity colleges with program-costweighted operating funds per FTE with and without performance funds included. ........144 4-30 Lorenz curve 2005-2006 for Florida co mmunity colleges with program-costweighted operating funds per FTE with and without performance funds included. ........145 4-31 Lorenz curve 2001-2002 for Florida co mmunity colleges with non-program-costweighted operating funds per FTE with and without performance funds included. ........146 4-32 Lorenz curve 2002-2003 for Florida co mmunity colleges with non-program-costweighted operating funds per FTE with and without performance funds included. ........147 4-33 Lorenz curve 2003-2004 for Florida co mmunity colleges with non-program-costweighted operating funds per FTE with and without performance funds included. ........148

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14 4-34 Lorenz curve 2004-2005 for Florida co mmunity colleges with non-program-costweighted operating funds per FTE with and without performance funds included. ........149 4-35 Lorenz curve 2005-2006 for Florida co mmunity colleges with non-program-costweighted operating funds per FTE with and without performance funds included. ........150 4-36 Lorenz curve 2001-2002 for Florida co mmunity colleges with program-costweighted operating funds per FTE with sp ecial population demogr aphic adjusted and non-special population dem ographic adju sted performance funds included...................151 4-37 Lorenz curve 2002-2003 for Florida co mmunity colleges with program-costweighted operating funds per FTE with sp ecial population demogr aphic adjusted and non-special population dem ographic adju sted performance funds included...................152 4-38 Lorenz curve 2003-2004 for Florida co mmunity colleges with program-cost weighted operating funds per FTE with sp ecial population demogr aphic adjusted and non-special population dem ographic adju sted performance funds included...................153 4-39 Lorenz curve 2004-2005 for Florida co mmunity colleges with program-costweighted operating funds per FTE with sp ecial population demogr aphic adjusted and non-special population dem ographic adjusted operating performance funds included... 154 4-40 Lorenz curve 2005-2006 for Florida co mmunity colleges with program-costweighted operating funds per FTE with sp ecial population demogr aphic adjusted and non-special population dem ographic adjusted operating performance funds included... 155

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15 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy FISCAL EQUITY AND THE EFFECTS OF CHANGES IN DEMOGRAPHICS ON PERFORMANCE FUNDING IN TH E FLORIDA COMMUNITY COLLEGE SYSTEM, 2002-2006 By Conferlete Carney May 2008 Chair: Dale F. Campbell Major: Higher Education Administration With higher education costs rising faster than the Consumer Price Index, policymakers are concerned that costs will affect access to education. They are concerned that federal and state support may be unable to keep pace with rising costs. Parents and students are concerned about rising student fees. Higher educ ation administrators are conc erned about funding equity and quality of education. The Spellings Commission Report of 2006 focused national attention on changing demographics and the need for higher education to educate citizens more effectively, especially minorities and other special populations. The Commi ssion Report states that as higher earning, highly educated baby boomers reach retirement age, the workforce needed for continued U.S economic growth will require minorities and othe r populations to backfill high-skill positions being vacated by baby boomers. Currently, these special populations are least educated, lower earners, and smaller per capital tax paye rs. This issue is of grave concern. Previous research studies in the State of Florida found declining equity in community college per-student FTE revenue distributions when performance funding is included. Only one of the previous findings was si gnificant at the confidence leve l of 95%. This 2007 research study

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16 addresses questions of horizont al fiscal equal with performa nce funding included, excluded, and indexed to special population de mographics in college serv ice areas. This study found the following: (a) evidence of improving equity in 2005-06 owing to funding formula-driven equalization enhancements implemented that year, (b) overall declining e quity for three of the equity statistic tests significant at the 95% confidence leve l when performance funding is included, and (c) that pe rformance funding indexed to special populations in college service areas is not a complete solution to funding equi ty, but may warrant further research. The study also contributes to horizontal fiscal equity theory by shedding new li ght on the effects of calculating the Gini coefficient equity statisti c with weighted full-ti me-equivalent student enrollment.

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17 CHAPTER 1 INTRODUCTION The financing of higher education has been a long-standing topic of debate in America. Beginning in the early 1800s, state legislatures throughout the nation withdrew funding subsidies from private colleges and universities following the Dartmouth College case of 1819 (The Trustees of Dartmouth College v. Woodward, 1819). The ruling set into motion the creation of the public universities in states such as Mich igan, Indiana, Wisconsin, and California. Later, Justin Smith Morrill, a congressman from Vermont during the 1860s, envisioned government financing of education for all social classes. Morrills so-called Land Grant College Act of 1862 passed in the United States Congress despite previous opposition from the southern states (Harderoad, 1987). Today, financing higher educati on continues to be debated. The Spellings Commission Report The 2006 Spellings Commission Report, which focuses on access, affordability, quality, and accountability, is the recent example of the hi gher education funding debate, and the impact that financing higher education has on the viab ility of Americas economy. Spelling (2006) states well the growing policy dilemma for continued adequate funding of higher education to meet national imperatives: Colleges and universities must continue to be the major route for new generations of Americans to achieve so cial mobility. And for the country as a whole, future economic growth will depend on our ability to sustain excellence, innovation, and leadership in higher education. The commission notes with concern the seem ingly inexorable increase in college costs, which have outpaced inflation for the past tw o decades and have made affordability an ever-growing worry for students, families, and policymakers. Too many students are either discouraged from atte nding college by risi ng costs, or take on worrisome debt burdens in order to do so. While students bear the immediate brunt of tuition increases, affordability is also a crucial policy dilemma for those who are asked to fund higher education, notably federal and state taxpayers. Even as instituti onal costs go up, in recent years state subsidies have decreased on a per ca pita basis and pub lic concern about affordability may eventually contribute to an erosion of confidence in higher

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18 education. In our view, affordability is directly affected by a financing system that provides limited incentives for colleges and universities to take aggressive steps to improve instituti onal efficiency and productivity (U.S. Department of Education, 2006, pp.1-2). The Importance of Higher Education Contrasting the long-standing debate on hi gher education funding, the importance of higher education itself is rarely debated. Higher educations role in helping individuals achieve a successful professional career, living a good life, and carrying out family responsibilities has been instilled in most Americans at one time or another. The value of higher education to Americas ability to compete in todays know ledge-based, global economy is not disputed. Authors of the Spellings Commission Report co ncurred and pointed out that, it is no exaggeration to declare that highe r education in the United States has become one of our greatest success stories (U.S. Department of Education, 2 006, p. vi). It can be ar gued that the greatness of America is owed as much to the importan ce placed on higher education as it is to the democratic principles of its government. Community colleges, in particular, have l ong been recognized for producing life-changing learning opportunities for people of all popula tion groups and academic abilities. American community colleges serve a unique mission of ope n access and of reaching out to all citizens (Cohen & Brawer, 2003). They have educated milli ons of Americans who otherwise would have been denied the opportunities fo r education and a better life (Eisenhower Commission Report, 1957; Cohen & Brawer, 2003). This is especially tr ue for community colleges role in educating Americas under-represented a nd non-traditional student popul ations (Cohen & Brawer, 2003). In addition, American community colleges have fr equently been called upon to respond to the nations demand for improvements in social und erstanding and skills for technical competence (Eisenhowers Commission Report, 1957; Witt, Wattenbarger, Gollattscheck, & Suppiger,

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19 1994). Today, social and technical skills are more crucial than ever before given the rapid changes in American demographics and the kno wledge-based global economy (U.S. Department of Education, 2006). Concerns About Education Quality and Costs Despite the achievements of American uni versities and community colleges, public confidence in the quality, cost effectiveness, a nd return on investment fr om higher education is eroding (National Commission on Excellence in Education, 1983; Roueche, Johnson & Roueche, 1997; U.S. Department of Education, 2006; Wingspread Group on Higher Education, 1993). A number of factors continue to contribute to the declining public confidence in higher education. Central among those factors are in creasing costs, eroding quality of outcomes, and the impacts of changing demographics (Campbell, Leverty, & Sayles, 1996; Honeyman & Bruhn, 1996; Leslie & Fretwell, 1996; U.S. Department of Education, 2006; Vaughan, 2000). The Spelling Commission concerns about the quality of American higher education is supported by several other landmark reports and di stinguished authors. Terry OBanion contends that The publication of A Nation at Risk in 1983 triggered one of the most massive educational reform movements in the history of education (OBanion, 1997, p. xiii). The report warned that, the educational foundations of our society ar e presently being eroded by a rising tide of mediocrity that threatens our very future as a nation and a people (National Commission on Excellence in Education, 1983, p. 5). The Nation at Risk Report (1983) cited complaints from business and military leaders about the high cost of providing remediation to workers; recruits who lacked basic verbal and computational skills; and significantly growing evidence that American students performed behind their international counterparts in most measures of academic achievement. Leslie and Fretwell (1996) echoed the concerns cited in the 1983 Nation at Risk Report. In their book, Wise Moves in Hard Times they asserted that there is a crisis of confidence, a

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20 crisis of values not just a fina ncial crisis. The American public values higher education and wants it to be universally available but the public also wants higher education to be responsive and responsible to the real needs of real people (p. xiii). Educational costs have been rising faster than inflation and family income (Leslie & Fretwell, 1996). Comprehensive, costly academic programs require prudent fiscal management and allocation of essential financial resources (Boone, 1997; Campbell, Leverty, & Sayles, 1996; Leslie & Fretwell, 1996; Vaughan, 2000). Shifts in Higher Education Funding In parallel with the increasing costs of hi gher education, much of the burden of funding higher education has shifted from the federal gove rnment to states and students in recent years (Leslie & Fretwell, 1996). In 1980, the federal government provided 15 % of higher education revenues (Finn & Manno, 1996). The federal perc entage decreased to 12% in 1993 (Finn & Manno, 1996). The shift of funding from the federal to state governments has been driven in part by the philosophy of smaller, more efficient fe deral government (Leslie & Fretwell, 1996). As the funding of higher education has shifted to the states, colleges and universities must compete with other state priorities, agencies, and programs for their f unding. Leslie & Fretwell (1996) refer to this phenomenon as the cro wding out effect on higher education funding, resulting in reduced allocations to educa tion (Honeyman & Bruhn 1996; Leslie & Fretwell, 1996). Moreover, funding for higher education in many states is a discretionary budget item, and the pattern of funding for higher education varies unpredictably with the changing needs of other state-level priorities (Yancey, 2002). As higher education funding sh ifted to the states and public concerns for quality grew, state legislators began calling for more account ability (Neal, 1995). State officials have increasingly demanded that higher education institutions implement performance and

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21 accountability measures (Leslie & Fretwell, 1996; Roueche, Johnson & Roueche, 1997; Wingspread Group on Higher Education, 1993). However, because the development of accountability measures was found to be costly, complex, and inconsistent, the accountability measures of the 1980s gave way to perfor mance indicators in the 1990s (Ewell, 1994a). Rising Student Tuition Costs The rising costs of student tuition and fees ar e also contributing to the erosion of public confidence in higher education. In 1988, 74% of community college funding was appropriated from federal, state and local sources, while 22% was obtained from tuition & fees (Honeyman, Williamson, & Wattenbarger, 1991). By 1993, 40% of all revenues for higher education came from federal, state, and local sources while tuition and fees accounted for 26.5% (Honeyman & Bruhn, 1996). Today, in the State of Florida, th e proportion of student tuition and fees is approximately 30.2% (Florida Community Colleg es & Workforce Education, Cost Analysis Report, 2005-2006). Students and parents concerns with the rising cost of higher education were addressed in Carnegie Foundation Reports during the 1980s and 1990s. In a 1999 Carnegie Foundation survey, data showed that by and large students viewed their unde rgraduate education as a means of developing skills that enabled them to la nd lucrative jobs in a technologically-oriented marketplace. However, the survey results indicate d that students as well as their parents were increasingly concerned about the costs associated with attending institutions of higher learning and what the payoff will be in good jobs afte r graduation (Baldwin, 2000). Students, parents, and taxpayers have come to understand that they often pay for an expensive education without receiving a fair value in return (Wi ngspread Group on Higher Education, 1993).

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22 Rapid Changes in American Demographics The rapid changes in American demographics are another concern and important factor for consideration in funding American higher ed ucation. Authors Thompson, Wood & Honeyman pointed out that economic woes coupled with rapid increases in nonwhite populations and dramatic restructuring of family units, signs of internal stress have become especially noticeable (Thompson, Wood & Honeyman, 1994, p. 12). While the economic stress and social costs of changing demographics in America are well documented (Thompson, Wood & Honeyman, 1994), th e Spellings Report pl aces the effects of demographic changes central among problems fa cing America today. The report updates anew the deficiencies in higher educa tion graduation rates, future proj ections for per-capital income, and education attainment in general. It states : The consequences of these problems are most severe for students from low-income families and for racial and ethic minorities (U.S. Department of Education, 2006, p. vii). The co mmission urges us to consider new goals for addressing Americas demographics in higher education now: We want postsecondary institutions to adapt to a world altered by t echnology, changing demographics and globalization (p. viii). Performance Based Funding With growing public concerns about the co sts and performance of higher education institutions, states began to embrace the concep ts of performance-based funding during the late 1980s and 1990s. Yancey (2002) points out that the implementation of performance in budgeting for higher education was not far behind it implementation in other government sectors (p.19). Many states required that at least pa rt of state funding to colleges be based on performance and accountability measures. The St ate of Tennessee enacted legislation requiring performance-based funding in 1987. By 1997, thir teen states had a dopted laws requiring

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23 appropriations funding on the basis of performan ce and accountability. Seventy-two percents of the states linked performance to the budgeting process for hi gher education by 2001 (Burke & Minassians, 2001; Yancey, 2002). The Concept of Equity The concept of equity as a major issue in hi gher education finance also emerged during the 1980s (Albright, 1996; Honeyman & Bruhn, 1996; Lesl ie & Fretwell, 1996). State legislators have long sought to adequately and equitably distribute state revenues to higher education (Boone, 1997; Vaughan, 2000; Yancey, 2002). Funding form ulas were developed to assist these objectives of state legislators beginning in the 1980s (Brown, 1999; McKeown, 1986, 1996; Yancey, 2002). State legislators struggled to develop optimal funding methodologies & criteria for judging methods & equity, as financial st ress increased (Martorana & Wattenbarger, 1978; Yancey, 2002). Equity within higher education is affected by a number of fa ctors, but particularly by the allocation of limited state funds among the majo r delivery systems of K-12 public and private schools, community colleges, and the university system. When the State of Florida citizens voted to support the Class Size Amendm ent in 2002, the pattern of funding allocations shifted from community colleges and universitie s to the K-12 delivery system. The shift in available state funding toward th e K-12 system has increased concerns about equity in allocation of state funding among Fl orida community colleges. Since the current funding formula for Floridas community college sy stem is driven largel y by instructional costs and full-time-equivalent (FTE) student enro llment, uneven FTE enrollment growth rates adversely affect equity among colleges in th e short run (Yancey, 2002). To address this unequalizing effect on equity among Floridas co mmunity colleges, stat e legislators in 2006-2007 appropriated $10 million dollars in support to commun ity colleges specifically to begin a process

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24 of equity compression. The ju stification of the compression / equalization funding is as follows: The Community College System has recognized a disparity in funding institutions based upon the funding gene rated by the Funding Model. The range as a percent of the funding formula standa rds currently stands at approximately 11.42 percentage points. A target rang e level of equalization would be approximately 5%. A certain amount of equalization / compression will occur naturally as funding is distributed ba sed on the funding model. However, the process would be accelerated by provid ing targeted funds to the most underfunded institutions. The requested increase of $10,000,000 would lower the range of equalization from 11.42 to 6.8 pe rcentage points (Flo rida Association of Community Colleges Council of Presidents Meeting, 2005, p. 3). The equity compression dollars, although base d on allocation indexes derived from the community colleges main funding formula, were allocated outside the main funding formula. While community college leaders, state legislators, and state agencies overseeing community colleges applaud and support results of the FCCS funding formula, a very high level of state and college attention remains on funding equity among the colleges (Florida Association of Community Colleges, 2005). Florida also utilizes a separate method to incentivize and reward education outcomes and productivity. In 1995-1996, Florida implemented performance-based budgeting (PBB) for a small portion of overall state s upport funding to the community colleges (Brown 1999; Yancey, 2002). These PBB allocations were based on performance measures and indicators, meaning that Florida actually uses a combina tion PBB/Performance funding alt hough the funds are referred to as PBB funds (Yancey, 2002). Since its implemen tation in 1995-96, the first official year of implementation, approximately $100 million dollars have been distributed to the community colleges.

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25 Previous Equity Research Findings Two studies have been conducted on the effects of performance-based funding on community college funding equity in Florida. The findings of the stud ies are as follows: (1) Based on the calculations from the six horizontal equity measures, Floridas funding formula for the 28 public community colleges was more equitable in school year 1994-95 prior to the implementatio n of performancebased funding than for all public comm unity colleges in 1996-97 (Brown, 1999, p. 108). (2) Results indicated that when perfor mance-based funding became close to 12% of total revenue, equity began to shift for the worse. When performancebased funding was 25% or higher of total re venue, the degree of equity in the funding formula decreased (Brown, 1999, p. 109). (3) Of the six statistical measures, only th e restricted range indicated a trend in equity that could be supported statistic ally at the 95% confidence level. That trend was an increasing restricted range over time, indicating decreasing equity in the system (Yancey, 2002, p. 141). (4) the evidence indicated that, except fo r range-related statistics, equity within the system remained relativ ely consistent throughout the period. Implications for policymakers are that a base-plus funding methodology, such as is used in Florida, will tend to maintain a consistent level of equity given a relatively stable environment (small a nnual changes in enrollment and total funding) (Yancey, 2002, p. 148). For the 2007-2008 budget, Floridas community college leaders and state agencies are requesting that an additional $10 million dollars be allocated for performance-based funding. Over the next three years, Floridas state agen cies for community colleges have proposed to request an additional $10 million each year, raisi ng the total annual state support of performancebased funding to a projected $50 million dollars to be allocated among Florida community colleges. In addition, a Performance-Based Budge t Subcommittee was formed in 2006 to make recommendations on the allocations of the pr ojected $50 million dollars among the performance measures and indicators. Having completed phase 1 of its charge, the Performance-Based Budget

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26 Subcommittee began in 2007 debating the merits of a ten-year plan to move performance funding up to 10 percent of total funds available. In light of the findings of the two previous re search studies and considering the charge of the PBB Subcommittee, several questions regarding the appropriateness of the current measures and allocations have emerged. Su ch questions include: What cha nges in measures, indicators, and/or weights should be considered? What should be done about the current mismatch in performance inputs and outcomes relative to the actual funding received by the colleges? and How will changes in demographics and enrollment patterns impact indicators of outcomes and fiscal equity among Florida Community Colleges? Purposes of the Study The purposes of this study were to examin e f iscal equity in the Florida Community College System (FCCS) during the five-year period of 2001-02 through 2005-06 and to explore possible improvement methods. The second purpose is to explore adjustments to performance funding that might lead to improved equity wh en performance funds are included in other operating revenues to the colleges. In particular, the second purpose is to explore the effects of indexing performance funds appropriated to the colleges for the purposes of incentivizing and rewarding them for degree completers among Black Males and Hispanics. Research Questions Two research questions are examined and expl ored in this study. Research question one centers on discerning whether hori zontal fiscal equity in perstudent FTE funding distributions to the colleges im proved, worsened, or remained unchanged over the five years of the study. The second research question explores one met hod of possibly increasing fiscal equity in funding distributions when perfor mance funds are included.

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27 (1) What influence did performance-based funding have in the changes in horizontal equity in the distribution of operating funds for Fl oridas 28 public community colleges for the years 2001-02 through 2005-06? (2) What effects will indexing the appropriations of applicable performance funds to the proportions of selected speci al population groups Black Males and Hispanics have on horizontal equity in the dist ribution of operating funds for Floridas 28 public community colleges for the years 2001-02 through 2005-06? Significance of the Study Policymakers and state legislators are likely to c ontinue to seize the call for accountability to strengthen mandates for performance improvement s in higher education. State legislators will increasingly consider improveme nts in cost efficiencies, grad uation rates, and other student success indicators in their budgetary and appropriation decisions. As they increase performance funding to incentivize improvements, expansion of the performance funding / horizontal equity knowledge-base will benefit their budgetary and appropriation decisions. This study will build on the existing knowledge-base rega rding the effect of performa nce funding on horizontal equity among Floridas community colleges. The study will also provide e ducational leaders and policym akers with new equitable funding approaches to incentivi ze improvements in ethnic minority graduation and achievement outcomes. The decline of Americas position am ong industrialized nations in graduation and student achievement, the predicte d relative decline in America s standard of living, and the national shift in ethnic demographics will increasingly be seen as a national economic imperative. Consequently, the increase of et hnic minority graduation and achievement outcomes will likely be perceived more as a national economi c imperative than a soci al justice issue. The results of this study may provide suggestions to educational leaders, policymakers, and legislators concerning how to increase incentives for ethnic minority educational outcomes while closing the existing equity gap am ong Florida community colleges.

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28 Definition of Terms The following definitions are to p rovide clarif ication and a foundation for interpreting this study. The definitions apply only for the purpose of this study. State support funding in this study is defined as the aggreg ate of four specific funds. Community colleges in Florida received opera ting funds from the st ate from four major appropriations categories duri ng the period analyzed: Comm unity College Program Fund (CCPF) General Revenue, CCPFLottery, Performance-Based Budgeting (PBB), and the Workforce Development Education Fund (WDE F). In the 2003-2004 appropriations session, total WDEF funding was rolled in to CCPF General Revenue. State support funding for the purpose of this study is the aggregate total of all four. The combination of state support funding and f ee revenue is considered total available operating funds for the purpose of this study. Students in Florida community colleges are pr edominately part time. In order to compare total available funding per student, a full-time course load for a Florida community college student is equal to 30 semester credit hours pe r year. Therefore, tota l semester credit hours enrollment for each institution is divided by 30 to determine the institutions full-time equivalent (FTE) enrollment. For the special population demographic adjust ment research question, college-age Black males and college-age Hispanics are defined as age-groups 18-55 in this study. The average age of students in Florida commun ity colleges is approximately 29. Many community college students work part-time or full-time jobs. Horizontal equity has been defined in the res earch literature as equal treatment of equals (Jones, 1985, p. 56). The term is also used in litera ture to refer to equal tax burdens for taxpayers with equal ability to pay, or it can mean that students who have equal educational needs should

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29 receive equal shares of education funding. The latter concept is the one used in this study (Berne & Stiefel, 1984; Brown, 1999; Harrell, 1992; Jones & Salmon, 1985; Yancey, 2002). Vertical equity has been defined in the research literat ure as unequal treatment of unequals (Jones, 1985, p. 56). The term is also used in the literature to refer to unequal tax burdens for taxpayers with unequal ability to pa y, or it can mean that students who have unequal education needs should receive unequal shares of education funding. The latter concept is the one used in this study (Berne & Stiefel, 1984; Brown, 1999; Harrell, 1992; Jones & Salmon, 1985; Yancey, 2002). Performance-based budgeting is defined in lite rature as funds distributed to colleges and universities with consid eration of performance but without tying designated funding amounts to performance on specific indica tors (Burke & Serban, 1998d). Performance-based funding has been defined in the research literatur e as special state funding tied directly to the achievements of public college s and universities on specific performance indicators (Burke & Serban, 1997a, p.1). Since the funding is tied directly to achievements, it is awarded after the achievements are performed. This is the distinction used in this study. In this research study, the term, statistics, is used to indicate a measure of the construct equity. The term, statistics, refers to a set of methods and rules for organizing, summarizing, and interpreting information (Gravetter & Walln au, 2002). Gravetter and Wallnua (2002) also distinguished between the plural use of the term, statistics, as a general reference for the entire set of statistical procedur es, and the singular use, statistic, as a specific type of statistical method (p. 3). This background on the terms, statistics and statistic, provides an important framework for

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30 the examination of the numerous statistics to be employed for measuring equity in financing of public schools. Limitations This study is limited to the Florida Comm unity College System com prised of 28 geographically separated and administered coll eges. Although the individual colleges have separate administrations, the system has a st ated goal of a common academic mission, common funding objective, and common f unding methodology for all institutions within the community college system (Harrell, 1992, p.11). The data were limited to the period of five fiscal years from 2001-02 to 2005-06. Neither private community colleges in Florida, public/private community colleges of any state, nor public/private unive rsities of any state were considered. Consequently, the funding equity analysis results cannot be generalized to any other state. The study is limited to state support funds and student fee revenue for general operating purposes. The total available operat ing revenue variable will be lim ited to student fees and state support funding because Florida community colleg es receive 64.1% of their operating funds from the state; 57.6% from general revenue funds and 6.5% from lottery funds. 30.2% percent of their operating funds come from matriculation and student fees leaving less than 6% from other revenue sources (2005-2006 Cost Analysis Report ). Other funds, such as Public Education Capital Outlay Trust Funds, building construction-related Capital Outlay & Debt Service Trust Funds, foundation contributions, donations and endowments, will not be included. The study is limited to the six disparity m easures developed for public school finance studies and focuses specifically on the concept of horizontal equity. Th e concept of vertical equity was addressed only to the extent that different weights were used for funding certain academic programs in recognition of the fact that some academic programs have higher costs and

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31 therefore should be funded at higher levels in or der to be equitable. The dependent variable will be limited to appropriation funding per FTE. Questions related to the adequacy of stat e support funding or the burden of fees on students and parents will not be addressed.

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32 CHAPTER 2 REVIEW OF RELATED LITERATURE In this chapter an overview of the literature relevant to this study is presented. The literature review focuses on implications of changing dem ographics to American higher education, accountability in higher education, performance f unding, equity in funding, the traditional statistics for measuring equity in per-student revenue distributions, and the concept and affects of weighted and un-weighted pupil count s on the Gini coefficien t equity statistic. The topics progress from the general concepts related to American higher education funding programs to those most specifically related to Florida community colleges. The Changing Demographics of America The changing demographics of Am erica have profound implications for Americas higher education and economic future. Writers T hompson, Wood and Honeyman (1994) addressed these implications for school missions, pedagog y, productivity and funding. Borrowing heavily from the work of Harold Hodgkinson (1985), Thompson et al. observed for the first time in American history, the nation is experiencing demographic changes that have profound implications for change in Americas fundament al social and economic structures and, that coupled with the effects of shifts in immigrati on, the combination of age, births, and family status, is the future (1994, p. 12). They further note that: Total immigration in the three majo r racial groups has experienced great shifts. The impacts of these shifts is a pparent in the 1990 census, showing that whites account for only 31% of total population, while the largest majority groups African-Americans and Hispanics comprise nearly 50%. Population projections suggest greate r change, as white populati on is expected to shrink rapidly. By A.D. 2000, the nations blacks are expected to n early double to 44 million; Hispanics are expected to triple to 47 million, many young and unskilled (pp. 12-13).

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33 The relevant points of Thompson, Wood and Hone yman observations are: (a) the shift in population towards a higher proportion of blacks a nd Hispanics, (b) their relative skill-levels, and (c) the profound implications for Am ericas schools and economic structure. Again drawing heavily from Hodgkinson, they go further to addre ss the educational implications of the new demography, as follows: Hodgkinsons observation that the future is the combination of age, births, and family status combined with immigration to create profound implications for schools in terms of mission, pedagogy, productivity, and of course, funding. Much of the na tion was built on the hope of oppressed peoples who accepted an invitation to become part of a new land of promise. Yet never before has the nation faced such formidable challenges; equally important, never before has any generation had reason to expect less from the future than its parents could expect. For many Americans, however, a declining life-style looms because the new demography does not contain a majority equipped to prosper in a postindustrial economy. For schools, the implications are obvious: education has not eradicated soci al and economic differences among peoples, and its clientele is increasin gly made up of those whose social history leaves them at a disadvantage (p. 19). Thompson et al. conclude that the drastic changes in Americas demography will require American education to better prepare minority clientele for the nations workforce of the foreseeable future: The argument concludes that the missi on of schools has changed, and that the new mission must become widely accepted because the clientele no longer fit the historic mode l of education; and that a concerted effort must be made to bring the schools clients into the mainstream of social and economic prosperity if for no other reason than that these persons will comprise the bulk of the nations labor force for the foreseeable future (pp. 19-22). Spellings (2006) also cite the concern for the changing demographics of America. First, citing among the most concerning problems losing students in the pipeline; students not entering college due inadequate information and ri sing costs; and signs of college graduates not mastering reading, writing and thinking skills the Spellings Commissioners state: The

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34 consequences of these problems are most severe for student from low-income families and for racial and ethnic minorities. But they affect us all (p. vii). We want postsecondary institutions to adapt to a world altered by technology, changi ng demographics and globalization (p. viii). A Spellings Issue Paper goes further in examining the implications of changing demographics on Americas social and econom ic structures. The Issue Paper states: Substantial increases in those segmen ts of Americas population with the lowest level of education, combined with the coming retirement of the baby boomers the most highly educated generation in U.S. history are projected to lead to a drop in the av erage level of education of the U.S. workforce over the next two decades, unless states do a better job of raising the educational level of all racial/ethnic groups. The projected decline in educational le vels coincides with th e growth of a knowledgebased economy that requires most workers to have higher levels of education. In addition, a drop in the average level of e ducation of U.S. workers would depress per-capital pers onal income levels for Americans, in turn creating a corresponding d ecrease in the nations tax base. Summary: If current trends continue the proportion of workers with high school diplomas and college degrees will decrease and the per capita personal income of Americans will decline over the next fifteen years (Spelling Commission, Ninth Issue Paper, 2006, p. 1). The serious nature of the projected effect s of the changing demographics on America economic structure is obvious. The Spelling reports do provide hope stating that: The projected declines in educatio nal and per-capita personal inco me levels can be reversed, however, if states do a better job of increasing the educat ion of all their residents, particularly those populations that are growing fastest (p. 1). The data supporting the Issue Paper focuses on tw o revealing facts. Fact #1 is that the U.S. workforce is in the midst of a sweeping demographic transformation. From 1980 to 2020, the white working-age population is projected to decline from 82% to 635. During the same period, the minority portion of the workforce is proj ected to double (from 18% to 37%), and the Hispanic/Latino portion is projected to almost triple (from 6% to 17%). Fact #2 is that the

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35 greatest increase in population growth in the U.S. workforce is occurring among those racial/ethnic groups with the lowest level of education, while the group reaching retirement age is predominantly white with higher levels of edu cation. Spellings Ninth I ssue Paper data shows: In 2000, whites ages 25 to 64 are twice as likely as African-Americans to have a bachelors degree and almost three times as likely as Hispanics/Latinos. The educat ional gap between whites and Hispanics/Latinos (as measured by th e percentage of the working-age population with a bachelors degree or higher) has almost doubled over the last two decades growing from 12 percentage points in 1980 to 19 percentage points in 2000. Comparab le data are not available for 1980 for associates degree attainment by et hnicity. From 1990 to 2000, however, the patterns for associates degrees are similar to those for bachelors degrees: the percentage of each majo r racial/ethnic population that has achieved an associates degree or higher has increased, but AsianAmericans and whites have made faster progress than Hispanics/Latinos, African-Americans, and Native Americans (p.4). The Ninth Issue Paper notes: this demographic shift can be traced to two primary causes: larger numbers of younger Americans (ages 0 to 44) are ethnic minorities, and increasing numbers of white workers are reaching retirement age. Despite increasing levels of ethnic diversity in nearly all states, 90% of Hispanics/Latinos reside in just 16 states, and 90% of African-Americans live in 21 states (p. 3). Florid a is among those states in which ethnic diversity of Hispanics/Latinos and African -Americans is growing fastest. Florida Demographics Floridas population has grown very rapidly in recent decades. In 1950, Florida was the twentieth largest state in the United St ates, with a populati on of less than 3 million. By 2000 its population had grown to almost 16 million, a five-fold in crease that made it the fourth largest state in the nation (Florida Population St udies, Volume 40, Bulletin 148, 2007). By 2006, Florida had grown to an estimated 18.0 million; making Florida the fastest growing of the current four most populous states with a growth of 29.2 percent for the period (U.S. Census Bureau, Statistical Abstract 2007, Historical Statistics).

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36 The rapid growth in Florida population has b een accompanied by dramatic changes in the demographic composition of the population. Between 1950 and 2000, for example, the proportion of Floridas population younger than age 15 declined from 26.2 to 19.0 percent; the proportion age 65 and older rose from 8.6 to 17.6; and the proportion black declined from 21.7 to 14.6 percent. The Hispanic population increased from 6.0 percent of the total population in 1970 to 16.8 percent in 2000. Changes in demographic composition have been even greater for many counties than for the state as a whole (Florida Population Studies, Volume 40, Bulletin 148, p. 1). Population projections for blacks and Hispanics in Florida indi cate continued growth. The Florida Populations Studies Bulletin 148 indica tes that the non-Hispanic Black population in Florida was 15% of total in year 2000, grew to 16% in 2006, and will remain at 16% through year 2020. This represents a projected 3.84 million non-Hispanic Blacks out of a total projected state population of 23.6 million. The bulletin indicates that the Hispanic population in Florida was 17% of total in year 2000, grew to 20% in 2006, and will continue growing to 25% by year 2020. This represents a projected 5.9 million Hisp anics out of a total projected state population of 23.6 million (Florida Population St udies, Volume 40, Bulletin 148, p. 93-94). Available literature on the topic of how well Floridas higher education institutions serve their black and Hispanic populati ons indicates mixed results. Go rdon B. Van de Water, in his survey submission to the Education Commission of the States two-year study of states, reports the following: Currently, Floridas 9 public universities enroll approxi mately 100,000 FTE students, and its 28 community colleges approximately 200,000 FTE students. Within this enrollment, African American students ar e significantly unde rrepresented. Although approximately 20 percent of Floridas high sc hool graduates are African-Americans, they represent less than 14% of the full-time postsecondary enrollment and earned fewer that 7 percent of the degrees awarded in 1991-1992. Hispanics, on the other hand, are enrolled

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37 much more closely in proportion to their pres ence in the overall population and achieve degrees at rates similar to those of the Caucasian populat ion (Ruppert, 1994, p. 28-29). In another report published by the Florida Department of Education (FDOE), the proportions of blacks and Hispanics appear to improve somewhat from the Van de Water, in his survey submission. In the FDOE report, whic h is based on individual submissions by the 28 community colleges for fall term 1993, 1994, 1995, the proportions of blacks and Hispanics appear to improve. The FDOE report states: Advanced and Professional [A and P] was the most populous group, serving approximately 250,000 students each of these te rms. A and P was fifty-nine percent female and two-thirds white. The percenta ge of both black and Hispanic students increased slightly during this time frame (F lorida Department of Education, Community Colleges, A Comparison of Community College Student Demographics by Program Area, 2005, p. 3). It can be seen from the literature presen ted above that Floridas population is undergoing drastic changes in demographics as is that of the nation as a whole. Florida, too, is faced with the challenges of improving educational outcomes for its minority populations to support its continued economic growth in the future. Accountability in Higher Education The call for increased accountability in American higher education is not new. It began in the 1980s as internal education assessm ents by proactive institutions (Neal, 1995 p.6). Some researchers attribute the call for increased education assessments to proactive initiatives on the part of higher education leader s responding to findings of th e Wingspread Report (Wingspread Group on Higher Education, 1993 ) The Wingspread Report, with its now famous assessment of an alarming rise of mediocrity in Americas education was a wakeup call for accountability in higher education (Roueche, Johnson, Roueche, 1997). Neal (1995), however, described the accountability call as the accountability movement and a phenomenon of external

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38 intervention unknown to higher education in recen t times (p.5). Neal contends the primary thrusts of the 1980s education accountability movement were the need to prove worth, the challenge to rebuild credibility, and the necess ity to show responsiveness to disenchanted constituencies. The earlier assessments on the part of hi gher education institu tions to demonstrate proactive initiative gave way to trends toward state mandated assessment of higher education services (Ewell, Finney, & Lenth 1990). Ewell, et al. pointed out that assessment of educational outcomes is inextricably linked with accountability, and that the high ground of assessment was quickly seized in the late 1980s and early 1990s by state policymakers. Policymakers and legislators saw in assessment a powerful l evel for change for improving undergraduate education. Moreover, Ewells et al. research focused on the policy implications of the new accountability and provided a clear linkage between the new accountability and the call for improvements in the quality of education instruction: Current trends in how policymakers and higher educators approach a new accountability include seeing assess ment as a mechanism for actively shaping institutional agendas towards greater attention to instructional quality. External requisites for acco untability are based on three broad policy directives: reestablishing cr edibility, expanding the base of resources, and creating a vision for the future. In contrast, internal requisites for accountability also involv e three policy directives: recreating standards for student competence and achievement, sending a clear message on priorities, and revitali zing curriculum and instructional practice (Ewell, 1994a, p.1). In the external and in ternal requisites for accountability, Neal (1995) saw that an important interest of policymakers and legislators was expa nsion of resources for higher education. In the internal requisite, he saw inst itutions and education leaders fo cused on improvement of standards for student competence and achievement. Neal also pointed out another important trend in the 1990s, stating the call for accounta bility in the 1990s changed tone s. Public policymakers in the

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39 1990s seemed less interested in th e issue of instructional quality and more concerned with issues of productivity and efficiency (Neal, 1995, p.6). This statement implies that, while policymakers and legislators are supportive of re sources expansion, they were more concerned about productivity and efficiency as early as the 1990s. The September 2006 report from the Commi ssion on the Future of American Higher Education (Spellings Commission) again puts accountability at the center of attention for American educators and policymakers. The Co mmission examined four central issues in American higher education: access, affordability, quality, and accountability. It concluded that improved accountability is vital to ensuring the success of all the other reforms proposed in the Commissions report (U.S. Department of Education, 2006, p.4). Adding to Neals (1995) earlier linkage between accountability and instructiona l quality, the Commission established a clear linkage between education affordability, incen tives, efficiency, productivity, and performance benchmarks. The report stated: In our view, affordability is directly affected by a financing system that provides limited incentives for colleges and universities to take aggressive steps to improve institutional effi ciency and productivity. To improve affordability, we propose a focused program of cost-cutting and productivity improvements in U.S. postsecondary institutions. Higher education institutions should improve institutional cost management through the development of new performance benchmarks, while also lowering per-student educational cost by reducing barriers for transfer students (U.S. Department of Education, 2006, p.2). Clearly, the Spellings Commission report placed high premiums on improving access, affordability for lower income citizens, and learning outcomes for the future of American higher education. Improved cost-efficien cy, productivity, and performance measurements were again recognized as vital to the future success of American higher education.

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40 The 2005 State Higher Education Executive Officers (SHEEO) National Commission on Accountability in Higher Education, a forerunne r to the 2006 Spellings Commission, paralleled the Spellings Commission report on several vita l points. One area was the central role of accountability in American higher education. In its Accountability for Better Results A National Imperative for Higher Education, the SHEEO Commission sounded an alarming call for a fresh approach to accountability (State Higher Educa tion Executive Officers, 2005, p.6). Stating that accountability for better resu lts was imperative, the SHEEO National Commission argued vigorously th at America needs fresh new accountability mechanisms that provide dependable information to monitor resu lts, target problems, and mobilize the will, resources, and creativity to improve the performa nce of American higher education (State Higher Education Executive Officers, 2005, p. 6). The SHEEO Commission went on to provide the following chilling, but compelling, evidence w hy decisive action must be taken now: For over fifty years, speaker after speak er university pr esidents, business leaders, Presidents of the United St ates have praised our system of higher education as the finest in the world. But even as we bask in the afterglow of past achievements a starker reality is emerging on the horizon. For the first time in decades the United States no longer leads the developed world in the rate of co llege completion. In addition, large developing economies, especially China and India, are successfully educating thousands of scientists and engineers in order to compete in the global economy. One-fourth of low-income students in the top quartile of academic ability and preparation fail to enroll in college within two years of high school graduation. While more minorities and low-income students are enrolling, the majority of minority students do not graduate. Both the price students pay and hi gher education costs have grown persistently faster that the consumer price index. State support and federal programs like Pell Grants are incr easingly falling behind enrollment demand and inflation (State Highe r Education Executive Officers, 2005, p.6). Adding again to Neals (1995) earlier accountability i ssue of instructional quality linkage and the Spellings Commission focus on affordab ility, incentives, efficiency, productivity, and

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41 performance benchmark linkages, the SHEEO Commission added another key component that is germane to this study the linkage to budge tary decisions. In particular, the SHEEO Commission challenged state govern ors, legislators, state boards and executives of higher education to create statewide da ta systems across all levels of education to help inform policy and budgetary decision that will close achievement gaps and promote greater equity in allocating resources (State Higher Edu cation Executive Officers, 2005, p.7). Also germane to the focus of this resear ch study, both the Spellings National Commission on the Future of Higher Education and the 2005 SHEEO National Commission on Accountability placed major emphasis on minority and low-income student outcomes and the needs to: (a) improve the perfor mance of minorities and other populations in American higher education, (b) inform budgetary decisions, and (c) pr omote greater equity in allocating resources. First, both reports clearly tied the concept of accountability to budgetary decisions made at all levels of higher education, includ ing state governance, legislative, state boards, and executives. Secondly, the SHEEO Commission Re port established a clear and direct linkage between the role of accountability in higher ed ucation and the concept of equity in allocating resources for higher education. Thirdly, and equally germane, the reports from both Commissions tied accountability to the imperative of improving th e performance of American higher education. The national importance of higher education and the challenge to states and institutions to respond to issues of cost and improving perfor mance is further crystallized in the SHEEO correspondence to higher education leaders (Lingenfelter, 2006). It is clear that related literature is overwhelmingly in favor of accountability, af fordability, incentives, efficiency, productivity, and performance in higher education.

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42 The Concept of Performance in Higher Education There is an increasing qu antity of literature on the concept of performance in higher education since the emergence of the accountabil ity movement in the 1980s. Brown (1992) citing Albright and Ruppert, points out that performance measures were developed by the states legislature and coordinating boards to assess the c ontributions of higher education institutions to the goals of the state (p.46). Yan cey (2002) provides a more extensive coverage of the concept of performance. His coverage, citing the work of Burke & Serban, 1997b, and Albright, 1996, includes some of the earliest initiatives in federal government, The U.S. Government Performance and Results Act of 1993, and th e Tennessee Higher Education Commission (THEC) initiated pilot in 1974 aimed at exploring the feasib ility of allocating state funds on a performance criteria. Burke & Serban also provide an update on the trend towards allo cating state funds on performance criteria in a series of literatur e publications during the 1997-98 timeframe. In a survey report published by The Nelson A. Rockefe ller Institute of Govern ment, Burke & Serban report the following observations: Traditionally, states have funded campuses based on current costs, inflationary increases, and projec ted enrollment. These input factors reflect what institutions require in tax support rather than what states desire from public education. This practice ignores outputs and outcomes, such as the quantity r quality of co llege graduates or the research and service provided to the states or their citizens. The new approach links tax support to institutional results on perfor mance indicators that reflect state priorities. Budgeting has shifted fr om what states should do for their campuses to what campuses should do for their states (Burke & Serban, 1997, p 1-2). Burke & Serban (1998) predicted in the report of their second survey th at thirty-five states, or seventy percent, could have at least one of the two forms of funding higher education programs based on performance (p. 3).

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43 McLendon, Hearn and Deaton (2006) provide a more recent liter ary coverage of performance in higher education. They coin a new term of performance-accountability and examines three kinds of performance-accountability policies adopted in higher education during the period 1979-2002. McLendon et al. describes well the earlier accountability era and the new accountability era in public higher educat ion. In the earlier era, they state: The central question before policymakers was: Precisely which activities and functions of public colleges and universities (e.g., academic programs, budgets, tuition setting, and so forth) should be dictated by the state and which should be left to the discreti on of campuses? The accountability focus, therefore, was on the design of governance systems capable of effectively regulating the flow of cam pus resources and the decisions of campus officials (McLendon, Hearn, Deaton, 2006, p. 1). McLendon et al. go on to distinguis h the new accountability era: In this new accountability era, no longe r are structural arrangements or resource inputs the primary focus of state policymakers; increasingly, states are demanding performance by public colleges and universities. In scrutinizing outcomes, state policym akers have sought to influence institutional behavior for the purpose of improving institutional performance. For example, many states began experimenting in the 1980s and 1990s with new incentives system s designed to link campus resources with desired performance outcomes (McLendon, Hearn, Deaton, 2006, p. 1). Performance Budgeting, Funding, and Reporting In Higher Education As indicated, performa nce-based budgeting a nd performance-based funding has been used in financing American higher education for nearly two and a half decades. First used in the State of Tennessee in 1979 (Albright, 1996; Burke & Serban, 1998c), the growth in use of performance-based funding by the states is well chr onicled in literature an d doctoral dissertations (Brown, 1999; Harrell, 1992; Yancey, 2002). In its newsletter of October 1998, the Nationa l Council for Research and Planning stated that, performance-based funding and budgeting repres ent a dramatic departure from traditional budgeting which is generally based on current co sts, inflation, salary increases, enrollment

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44 levels, and special initiatives ( p. 10). Albright (1996) asserts that previously: (a) most financing systems focused on input factors average cost s or student/faculty ratios and (b) outcomes performance levels, quality, or out comes including student learning have generally not been considered. Albright (1996) we nt on to point out a new, emer ging trend of policymakers when she stated that, within the past few years na tional policy organizations including the National Governors Association and the Education Comm ission of the States have recommended that higher education budget allocations be linked with outcomes and state priorities (p. 1). Albright (1996) describes pe rformance-based funding for mo st states as a merged planning, budgeting, accountability system whic h allocates incentive funds, additional funds beyond baseline, to institutions for success in achieving statewide goals (p. 3). Burke & Serban (1998) also describe performance-based funding as separate and usually small allocations tied directly to the institutions results. The later authors distinguish performance-based budgeting as an indirect linkage to institutional perform ance, where the link between performance and resource allocation is flex ible but unclear (p. 2). McLendon et al. (2006), continuing on the them e of the new accountability era, agree with the above descriptions put forth by Albright, Burke & Serban, and adds a third form: performance reporting. They describe performanc e reporting as having no formal linkage to resource allocations, but relies on informa tion and publicity to encourage colleges and universities to improve their pe rformance (p. 2). McLendon et al ., citing Burke and associates annual survey findings, report that as of 2003, 25 states had adopted performance funding programs; 35 states had adopted performance-based budgeting programs; and 42 states had adopted performance-reporting policy (p. 2).

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45 Among the strongest drivers for the increasing use of performance-based budgeting, funding and reporting are concerns with the quality of American higher education and increased taxes and government spending. McLendon et al. (2006) provide the most comprehensive summary of these concerns and drivers: Close observers have attributed this new focus on performance accountability in higher education to a variety of factor s. These factors include (a) st ructural change in the U.S. economy (e.g. globalization), wh ich brought pressure from the business community for campuses to maximize productivity and efficien cy; (b) recent shifts in the theory and practice of public-sec tor governance, which, in the name of reinventing government, valued decentralization, entrepreneursh ip, and greater emphasis on markets, competitiveness, and the measure of performance; (c) the extreme financial pressures placed on state governments in the 1990s, which intensified higher educations competition with other budget priorities fo r increasingly limited state discretionary dollars; (d) the reform movement in K-12 education which ratcheted up pressure for accountability across all educati onal sectors; (e) changes in state political leadership, which brought to office a new breed of elected official more sympathetic to the call for increased accountability in higher education; and (f) the failure of the earlier voluntary assessment movement in higher education to satisfy for these elected officials that public universities are capable on their ow n of meeting growing accountability demands (p. 2). Performance Measures in Higher Education Much of the literature on performa nce measures in higher education stem from the internal education assessment initiatives of the 1980s (Neal, 1995 p. 6, Ruppert, 1994, p. 2). Scholarly writers and researchers were larg ely interested in the following: what performance measures and indicators were being used in various states of America, differenc es and commonalities among the states, major categories of performance measures and indicators, and what constituents most influenced their development. Many scholars and researchers contri buted to this body of literature, and among the more prolific were Burke & Serban, Burke & Minassians, Albright, Ewell, Richardson, and Ruppert. Sandra Ruppert (1994), citing wo rk of Peter Ewell & Dennis Jones, and another work by Richard Richardson, provides a list of common performance indicators used among various

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46 states and three models for categorizing performance indicators and measures (p. 2). Using Ewell & Jones definitions, Ruppert shares that performance measures generally refer to reporting values stemming from the 1980s internal educat ion assessment initiatives of colleges and universities, while performan ce indicators refer to reporti ng values stemming from new accountability policies of the 1990s in which external state, students, employers, parents, and the general public concerns are reflected (p. 2). Aside from these dis tinctions, the literature suggests the terms are often used interchangeably. Yancey (2002), borrowing from Ruppert, lis ted the following twelve most commonly identified performance measures among ten case study states. These twelve most common are results of the 1993 Education Commission of the States (ECS) case study of ten most active states at the time. Yancey, although acknowledging broad differences among the states, lists the following as most commonly used base d on the ECS case study (p. 39-40): 1) Total degrees awarded by instituti on and program and time to degree 2) Enrollment/retention/graduation data by gender, ethnicity, and program 3) External or sponsored research funds 4) Admission standards and measures of first-year class against standards 5) Number and percentage of accredited and eligible programs 6) Total student credit hours produced by institution and discipline 7) Remediation activities and indicato rs of remedial effectiveness 8) Transfer rates to and from twoand four-year colleges 9) Pass rates on professional licensure exams 10) Placement data on graduates 11) Results of follow-up satisfaction studies (alumni, students, parents, employers) 12) Faculty workload/productivity data Yancey (2002) and Ruppert (1994) borrowing from Ewell & Jones, and Richardson, also explain three frameworks for cat egorizing performance measures and indicators, as follows. Richardson employs two models: (1) an input/output/outcome model; and (2) a quality definition model. By definition, inputs are baseline measures of instructional inputs a nd monetary resources (e.g., student faculty ratios, state a ppropriations per capita, and average class sizes). Outputs are measures of instituti onal production (e.g., course completion

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47 rates, total degrees awarded, and time-to-degree). Outcomes measure qualitative benefits to students a nd the state while taking into account institutional missions (e.g., student performance on nationally normed tests, placement of graduates, and results of alumni satisfaction surveys). In Richardsons second model, performance indicators are assigned to five categories of quality: (1) transcendent quality, through institutional rank or reputation; (2) cost/benefit quality, determined by comparing institutional inputs and outputs with system and institutional goals; (3) process-based quality assessed by examining output i ndicators with respect to explicit standards; (4) product-based quality as determined by measureable attributes of graduates; and (5) us er-based quality, measured by client satisfaction. Using the two models above, Richardson (a) obs erved that (a) states are currently more interested in output indicators th an inputs and show signs of a growing interest in outcomes, and (b) concludes that each definiti on in the quality categories mode l suggests ways of measuring quality by what is valued by various higher education stakeholders (Ruppert, 1994, p.3). Richardsons models provide the basis for a cl ear understanding of the role of performance measures and indicators in the contexts of (a) in ternal initiatives by colleges and universities and (b) productivity and efficiency goa ls of states and policymakers. Ewells model for categorizing performance indicators and measur es, which follows below, provide s a clear linkage to the focus of this study. In his analysis, Ewell lists performa nce indicators according to categories conforming generally to state goals a nd domains: (1) instructional quality (inputs, processes, outcomes); (2) gene ral efficiency and productivity; (3) condition of the asset; (4) diversity, a ccess, and equity; (5) articulation and K-12 linkages; and (6) relation to state needs (Ruppert, 1994, P.3). By observing closely the list of twelve most common measures and indicators, and Richardson and Ewell models, it can be seen th at concerns for ethnicity and diversity are common threads in each. In the list of twelve most common measures and indicators, #3 addresses enrollment/retention/graduation data by gender, ethnicity, and program. In Richardson

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48 model, demography and special pop ulations are implicit in output s measures of institutional production (e.g., course completion ra tes) and benefits to students. In Ewell model, category #4: diversity, access and equity, addresses demogr aphy and special populations more explicitly. These performance measures and indicators of hi gher educations productivity for the Americas changing demography and minority populations is evident as early as the 1990s, and are consistent with concerns set fort h in Spellings Ninth Issue Paper. Performance Funding in Florida Higher Education The foundation of current performa nce accountabi lity in Florida higher education is set forth in Florida legislative statutes. First set forth in 1991, the basic intents of current Florida performance accountability progra m are to (a) achieve system atic, on-going improvements in higher education quality and effi ciency, (b) assessment of those improvements, and (c) to address eight delineated issues of importance to the state at that time (Section 240.324, Florida Statutes). The basic intents a nd issues of importance conveyed for community colleges in the 1991 Statute have largely remained constant in the 2006 Florida Statutes, Chapter 1008.45 which reads as follows: It is the intent of the legislature that a management and accountability process be implemented which provides for the systematic, on-going improvement and assessment of the improvement of the quality and efficiency of the Florida Community College System. Accordingly, the State Board of Education and the co mmunity college boards of trustees shall develop and implement an accountability plan to improve and evaluate the instructional and admini strative efficiency and effectiveness of the Florida Community College System. This plan shall be designed in consultation with staff of the Gove rnor and the Legislative and must address the following issues: (a) Graduation rates of A.A and A.S. de gree-seeking students compared to first-time-enrolled students s eeking the associate degree. (b) Minority student enrollment and retention rates.

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49 (c) Student performance, including stud ent performance in college-level academic skills, mean grade point averages for community college student performance on state licensure examinations. (d) Job placement rates of community college career students. (e) Student progression by admission status and program (f) Career accountability standa rds indentified in s. 1008.42 (g) Institutional assessment efforts relate d to the requirements of s. III in the Criteria for Accreditation of the Commission on Colleges of the Southern Association of Colleges and Schools. (h) Other measures as identified by the Council for Education Policy Research and Improvement and approved by the State Board of Education. It is noteworthy to point out issue (b) above was con cerned with minority student enrollment and retention rates has remained constant from 1991 to 2006 confirming later observations of Van de Water about under repres entation of Floridas minority populations (Van de Water, 1994). It is also noteworthy to obser ve the key stakeholders highlighted in the 1991 and 2006 Florida statutes: the staff of the Governo rs office, the legislature, the State Board of Education, Boards of Trustees, and students. The foundation for the current performance budg eting/funding system for higher education in Florida is set forth by the Government Pe rformance and Accountability Act of 1994 (Yancey, 2002; Brown, 1999; Laws of Florida, Chapter 94-249, 1994). The Government Performance and Accountability Act of 1994 required the Di vision of Community Colleges to submit a performance-based budget in the fall of 1995 for implementation in the 1996-97 fiscal year. The State University System was to follow the s ubsequent year (Yancey, 2002, p. 56). Yancey goes on to explain in greater detail how two sepa rate performance budgeting/funding systems have actually existed in Florida co mmunity colleges since 1996/97. Th e two systems, although both called Performance Based Budgeting (PBB), is act ually a performance funding system according

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50 to Burke & Serbans earlier definition, where a llocations are tied directly to the institutions results (Burke & Serban, 1998). The two-syst ems called one (PBB) are the results of differences between the governors office and the state Senate on how to implement performance funding for higher education in Florida (Yancey, 2002, pp. 56-57). In the first year, 1996-97, the Florida Legi slature appropriated $12 million divided among three measures. Since 1996-97, the Legislature has funded PBB for the community colleges in varying amounts: 1997-98, $12 million; 1998-99 $4.8 million; 1999-2000, $8.1 million; 200001, $8.3 million (Yancey, p. 57). For the 4-year period 2002-2005, Florida PBB appropriations were held relatively constant at approxim ately $7.7 million, but increased in 2005-2006 to $18.1 million (Appendix A Raw Data, Florida Department of Education, 2007). The percentage of PBB to total funding appr opriated to Florida community colleges has remained miniscule, ranging from a low of 0.47% in 1998-99 to a high of 1.32% in 1996-97 (Yancey, 2002, p. 145; Table 5.10 this study). In 2007, the Florida Association of Community Colleges Council of President adopted a goal of incr easing the percentage of performance funding relative to opera ting budget [state funds] to 5% over the next five years (Florida Community College System Performance Funding Report, July 2007, p. ii). The report states: This will help insure that incentive levels for all programmatic areas are sufficiently compelling to focus local attention on monitoring and enha ncing all aspects of lo cal program performance The report also indicates the intent to service harder-to-serve students, and specifically states: including Black Males (an under-re presented population in the co mmunity college system), and Students whose native language is not English (p. ii). Performance Measures and Indicators in Florida Community Colleges As has been indicated earlier for Florid as performa nce account ability system, the foundation for Floridas performance measures a nd indicators are also set forth in Florida

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51 legislative statutes. The performance measures and indicato rs, however, are scattered throughout various statutes according to program areas. For example, the 2006 statutes for Workforce Education are set forth in 2006 Florida Statutes, Ch apter 1011, Part III. Relevant subsections of Chapter 1011, Part III read as follows: (4) Funding for all workforce education programs must be based on cost categories, performance output measures, and performance outcome measures. (b)1. The performance output measure for career education programs of study is completion of a career prog ram of study that leads to an occupational completion point asso ciated with a certificate; Performance output measures for re gistered apprenticeship programs shall be based on program lengths that coincide wit lengths established pursuant to the requi rements of chapter 446 [Florida Statutes]. Yancey (2002) points out that, from the begi nning in 1996-97, the Fl orida Legislature has allocated amounts of money each year to the colleges based on total points earned on three categories of measures: degree and certificate co mpleters; completers who are at-risk students; and completers who graduated with no more than 72 credit hours attempted (p. 57). The measures remained essentially the same from 1996-97 thro ugh 1997-98. In 1998-99, black males were added to the special populations in Measure II. Other changes in the measures were made in 1999-2000 and 2000-01, such as points given for partial completers of programs and for dual enrolled students (Yancey, p. 58). As of 2006, Floridas performance funding meas ures and indicators are categorized by funds and by measures. The performance fund ca tegories are: incentive funds, performance funds, and workforce programs funds. The incentiv e funds are further categorized into measures of efficiency time (time to degree) and colle ge preparatory program. Performance funds for AA degree programs are categorized into Measure I (o utputs), Measure II (Spe cial Populations) and Measure III (outcomes). Workforce funds are fo r AS degree programs, Ap prenticeship programs,

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52 Postsecondary Adult Vocational Programs, Adul t High School Programs, General Equivalency Diploma (GED), and Adult Literacy Program. Workforce funds are also categorized into Measures I, II, and III. The Florida Legislature a ppropriates fixed amounts of dollars to each fund and to each measure within a fund (Flori da Community College System, Performance Funding Report 2006-2007, September 2006). Funds are distributed among colleges based upon each colleges pro-rata share of the total system points earned in each fund program and measure category. Application of the Annual Cost Analysis and weighted completers fro m prior year determines the amount of dollars expended in the performance programs. This am ount is separated into measures using the following percentages: 40% for outputs, 20% fo r special populations, and 40% for outcomes. Weighted completers, indexed to a cost factor relative to an AA degree, are used for all programs other than Associate of Arts as the outputs for Measures I. For this 2007 research study, measure II (speci al populations) is particularly germane to research question two. In the performance funds and workforce funds, measure II includes graduates/completers who: requir ed remediation base on college pl acement test results; qualified as economically disadvantaged under federal guide lines; were reported as disabled using federal guidelines; is a Black Male, or; tested into English for Academic Purposes (EAP), Limited English Proficiency (LEP), or English for non-English Speakers (ENS). Special population graduate/completers are counted as separate indicator value points than non-EAP/LEP/ENS and non-Black male completers for input Measur e 1 and outcome Measures 2 and 3(Florida Community College System, Performance F unding Report 2006-2007, September 2006; Yancey, 2002; Brown, 1999).

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53 The Concept of Equity in Higher Education With the intensif ied competition with other di scretionary budget priorities at the state funding level, it is easy to s ee why equity in higher education funding became paramount for higher education leaders. However, the origin of equity in per-student re venue funding is not in higher education but in K-12 school districts. The literature revi ew reveals the origin and how per-student revenue equity becam e important in higher education. Author Kern Alexander (1982) distinguishes two significant categories of equity: commutative equity and distributive equity (p. 196). Commutative equity entitles a person to possession simply because the possession is owne d by the person by virtue of a private or individual relationship. Commuta tive equity does not affect th e distribution resulting from market place conditions. Conversely, distributive equity is the redi stribution of social benefits directly resulting from market place conditions or from governmental actions. Alexander asserts that it is distributive equity that issues of equality and public school finance most commonly arise. Citing Hayek (1976), Alexander states th e following regarding the role of government in assuring distributive equity. Hayek believes that equity is served if government does not grant benefits in unequal proportions to certain persons, to the detriment of others. The best result which government can effectua te is that all players in the game will have equal chances to succeed, or that legislation will not be responsible for determining who will win or lose. If government does intercede in the natural processes, cr eating imbalances and disparities in the opportunity to develop ones abil ities, then remedial action through legislation may be necessary to effectuate equity (p. 197). The work of scholar and resear cher Ellwood P. Cubberley is generally recognized as being among the first to apply the concept of equity to modern school finance (Thompson, et al., 1994). Cubberleys doctoral dissertation an d subsequent studies made four great advances to field of education finance, as poin ted out by Thompson, et al.:

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54 Cubberleys work thus made four great advances. First, his hypotheses were a giant step by stating the imp act of money on education. Second, in advocating the notion that all children in a state are entitled to the same advantages, he moved the focus of school funding into the fairness and justice arenas. Third, his subsequent studies confirmed his hypotheses by showing that some children were in deed disadvantaged by the extremely local nature of school funding. Fourth and perhaps most importantly, his advocacy for a state tax to more equally distribute the costs and benefits of education was an enormous stride in th at it marked the beginning of a shift from benevolence to active state resp onsibility for education (p. 212). Since the historic work of Cubberley, other th eorists and scholars have built on the concept of equity in education funding. Notable among th em are Robert Berne and Leanna Stiefel who proposed a framework for quantitatively measur ing equity in school funding. The framework established by Berne and Stiefel is organized ar ound the answers to the following four questions (Berne & Stiefel, 1984; Kearney & Chen, 1989; Sample & Hartman, 1990): 1) Who? What is the makeup of the groups for which school finance systems should be equitable? 2) What? What services, resources, or, more ge nerally, objects should be distributed fairly among members of the groups? 3) How? What principles should be used to determine whether a partic ular distribution is equitable? 4) How much? What quantitative measures should be used to assess the degree of equity? Answers to each of the four questions estab lished in the framework are germane to and used in this 2007 research study. In most studies of higher educati on funding as is the case in this study the answer to question one is full-tim e-equivalent (FTE) studen ts in each school. The answer to question two is per-student revenue funding to each school. Also germane to this study is the answer to que stion three; namely, the principles to use in determining whether a particular per-student revenue funding dist ribution is equitable or not. Berne & Stiefel stresses that once a particular obj ect is such as inputs per pupil is selected, one

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55 must then apply an equity principle in order to draw conclusions on whether the object is distributed fairly (p.13). They go on to describe three broad principles thought to encompass all of the definitions of equity for children and students in funding dist ributions. Those three principles are: Equal Treatment of Equals, or Horizontal Equity; Unequal Treatment of Unequals, or Vertical Equity, and Equal O pportunity (p. 13-17). Although the framework established by Berne & Stiefel was first applied to studies of K-12 school district finance, they have since been widely used and established in studies of equity in higher education funding distributions (Yancey, 2 002; Brown, 1999, Harrell 1992). Statistics for Measuring E quity in Public Schools Statistical me thods for analyzing equity in public schools are well chronicled and established in literature and previous research (Berne & Stiefel, 1984; Brown, 1999; Goertz, 1983; Thompson, Wood, & Honeyman, 1994; & Yancey, 2002). These previous authors and researchers affirmed the applicability of certain statistical methods for an alyzing equity in public schools based on their repeated use in rese arch studies (Yancey, 2002, p.73) and their well defined and generally accepted methodology for the measurement of equity (Cronk & Johnson, 1983, p. 502). Odden, Berne, and Stiefel (1979) also atte sted to the many stat istics that could be used to measure equity or inequity for any of the objects [e.g., per-student revenue] and any of the principles [e.g., equal treatment of equals] for either children [students] or taxpayers (p.18). Odden, et al. listed the following eleven statistics that have been used in at least one analysis of equity in school finance: 1) The range the difference between the highest and the lowest. 2) The restricted range the difference between the 95th and the 5th percentiles. 3) The federal range ratio the restricted range divided by the value at the 5th percentile.

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56 4) The relative mean deviation the absolute va lue of the sum of the differences of each revenue figure from the sum of the differences of each revenue figures from the mean revenue, as a proportion of total revenue. 5) The McLoone Index the ratio of the actual revenues of students below the median to the total, if all students were at the median. 6) The variance the average of the squared de viations of the each revenue figure from the mean revenue. 7) The coefficient of variation the standard deviation divided by the mean. 8) The standard deviation of the logarithms the square root of the variance of the logarithm of revenues. 9) The Gini coefficient shows how far th e distribution is from providing each percentage of revenues (e.g., 5% of revenues). 10) The Theil measure based on the thermodynamic concept of entropy and shows how far each student is from receiving an equal share of revenues. 11) Atkinsons Index based on the economists idea of a social welfare function and capable of weighting the bottom end of the di stribution as much as desired (Odden, et al., 1979, p. 19-20). It can be seen from the brief definitions provided above, and by their formulas to be provided later, that each statisti c for measuring equity is differe nt and, according to Odden, et al. (1979) involves value judgments. Odden, et al extend the discussion beyond the recognition of numerous statistics for measuring equity by stating that each statistic has different characteristics and usually, diffe rent statistics lead to different conclusions about the degree of equity or inequity of the system (p.18). This extension opens a new area of research questions, including: What are the major differences in the characteristics of these statisti cs?; What is the curren t literature and views on statistics for measuring equity and inequity?; What different conclusions can be drawn for the same sets of data on equity in financing of public schools?; and Are previous research study conclusions justified? Therefore, this research study plans to ex amine current literature and re-

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57 examine conclusions of selected pervious research studies in the new light of current literature and inherent differences in statistics for measur ing equity in school fi nance. First, a more detailed examination of the statistics that ha ve been applied to community colleges will be pursued. Harrell (1992), Brown (1999), and Yancey (2002) established that six of the eleven statistics identified by Odden, et al. (1979) ha ve been applied to community college funding research. These statistics are de scribed in more detail below. Range The range is a m easure of variability in a distribution of values (e.g., per-pupil revenue). It is perhaps the simplest and most obvious way of describing how di spersed or spread-out values are in a given distribution. Gravet ter and Wallnau (2002) define ra nge as the difference between the upper real limit of the larg est (maximum) X value and the lower real lim it of the smallest minimum) X value (p. 78). When used in public school finance studie s, the range is the difference between the highest per-pupil revenue/e xpenditure (Berne & Stiefel, 1984). Described by Hickrod, Chaudhari, & Lundeen (1980) as the simple range, it has been used widely by public school finance researchers to study per-pupil revenue (Brown, 1999; Garris & Cohn, 1996; Hirth, 1994; Oesch & Paquette, 1995; Sample & Hartman, 1990; Stark, Wood, & Honeyman, 1993; Stiefel, R ubenstein, & Berne, 1998; Ve rstegen 1996; Yancey, 2002). If the calculated range between the highest and the lowest per-pupil revenue funding is small, then the funding distribution is equitable. Conversely, if the calculated range between the highest and the lowest per-pupil revenue fundi ng is large; the fundi ng distribution is not equitable. While the range statistic is simple, it has cer tain weaknesses which can affect conclusions drawn from it use. Grav etter and Wallnau (2002) pointed out that the problem with using the

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58 range as a measure of va riability is that it is completely determined by the two extreme values and ignores the other scores in the distribution. Becau se the range does not consider all the scores in the distribution, it ofte n does not give an accurate descri ption of the variability for the entire distribution. For this reason, Gravetter and Wallnau assert that the range is considered to be a crude and unreliable measure of variability (p. 79). Odden, et al. (1979) went even further to point out that the range is n ot inflation proof (p. 21). Yancey (2002) noted that the range is sensitive to inflation and that studies over time might show a large range that is simply a reflection of inflation rather than a true ine quity (p. 75). Accordingly, many researchers when using the range as a measure of equity in public school finance have compensated for inflation by using the Consumer Price Index (CPI) to adjust dollars for multiple year studies (Hirth, 1994; Yancey, 2002). Restricted Range The restrict ed range is also a statistics measure of variability in a distribution of values. The restricted range is used frequently in correlation statistical te chniques. However, the restricted range attempts to address the un-relia bility issue caused by the effects of outliers which are more inherent in the simple range statistic. Extreme outliers can have dramatic influences on calculation results. Because the ex treme outliers are eliminat ed from the restricted range calculation, researchers may derive im proved representations and conclusions about overall equity, so long as certain precautions are taken into considerati on. Gravetter and Wallnau (2002) caution that, because of the effects of outliers, research er should always examine the corresponding scatterplot when assessing the value of a correlation (p. 398). They also noted that, while the restricted range provides an improved representation of a distribution, it does not take into account other outliers that could be within the 95th and 5th percentiles of the distribution. Consequently, the re stricted range is considered a somewhat crude measure of

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59 variability; as is the range, interquartile ra nge, and semi-interquart ile range (Gravetter & Wallnau, 2002, p. 80, 398). As noted previously, the restricted range cal culates the difference between values at the 95th percentile and the 5th percentile of the distribution. No twithstanding the limitations of the restricted range statistic, it has been used to analyze per-pupil re venue equity in a number of research studies; and its use continues in many present-day research studies (Brown, 1999; Garris & Cohn, 1996; Hirth, 1994; Oesch & Paqu ette, 1995; Sample & Hartman, 1990; Stark, Wood, & Honeyman, 1993; Stiefel, Rubenstein, & Berne, 1998; Verstegen 1996; Yancey, 2002). Federal Range Ratio The federal range ratio, also a st atistics meas ure of variability, is used today in many public school finance publications by the National Center for Education Statistics (NCES). It has been described as the federal measure of disparity (Hickrod, Hines, Anthony, Dively, & Pruyne, 1980, p. 182; Yancey, 2002, p. 76) It is defined by researcher s as the restricted range divided by the per-pupil object as the 5th percentile of pupils (Berne & Stiefel, 1984, p.19; Hirth, 1994, p.174). More recently, researcher Johnson of the NCES, reflecti ng upon a calculation method directly from raw data, defined it as the difference between the amount of per student revenue at the 95th percentile and the amount of per student revenue at the 5th percentile divided by the amount at the 5th percentile (Johnson, 2006, p.12). The federal range ratio statistic offers some advantages over both the range and restricted range statistics. Hirth (1994) point ed out that, the federal range ra tio is not sensitive to inflation, which makes it a more acceptable range statistic than the range or restricted range (p.174). Yancey also noted advantages when he stated, expressing esse ntially the same information as the restricted range statistic, only in terms of a ratio, the federal range ratio overcomes the inflation problem (Yancey, 2002, p. 76).

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60 The federal range ratio continues to be used today in many current publications (Fowler, Jr., 1996; Johnson, 2006), and has been previously us ed in numerous studies of per-pupil revenue and expenditure equity, and it is still in use in many present-da y research studies (Brown, 1999; Fowler, Jr., 1996; Garris & Cohn, 1996; Hirth, 1 994; Johnson, 2006; Oesch & Paquette, 1995; Sample & Hartman, 1990; Stark, Wood, & Honeyman, 1993; Stiefel, Rubenstein, & Berne, 1998; Verstegen 1996; Yancey, 2002). Coefficient of Variation The coefficient of variation (C.V.) measures variability in a distri bution of values around the mean value in the distribution (King, 1983; Verstegen & Salm on, 1989). Therefore, it is a measure of variability, as are the range, restricted range, and federal range ratio. It is calculated by dividing the standard deviation of the di stribution by the mean of the distribution (Thompson Wood, & Honeyman, 1994, p. 248). Because the C.V. uses the standard deviation of the distribution and the mean of th e distribution in determining its va lue, it offers some analytical advantages over the range, restricted range, and federal range ratio. Gravetter and Wallnua (2002) point ed out that, the standard deviation uses the mean of the distribution as reference point and measures variability by considering the distance between each score and the mean (p. 81). They further co ntended that, the standard deviation is the most commonly used and the most important measure of variability (Gravetter & Wallnua, 2002, p. 81). The C.V. takes into consideration al l of the variation in the distribution by including both high and the low values in the distribution (Hickrod, Chaudhari, & Lundeen, 1980). Yancey also noted that, beca use the coefficient of variation is calcul ated by dividing the standard deviation by the mean, its value is al ways a decimal between zero and one (Yancey, 2002, p. 77). Therefore, the smaller the decimal va lues of C.V, the less variability among the values in the distribution and the more equ ity in per-pupil revenue in the distribution.

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61 Conversely, the greater the decimal values of C.V, the more variability among the values in the distribution and lesser equity in pe r-pupil revenue in the distribution. The coefficient of variation has been used in numerous studies of per-pupil revenue and expenditure equity, and its use continues in many present-day research studies (Brown, 1999; Cronk & Johnson, 1983; Hirth, 1994; Oesch & Paquette, 1995; Stark, Wood, & Honeyman, 1994; Stiefel, Rubenstein, & Berne, 1998; Verstegen, 1996; Yancey, 2002). McLoone Index The McLoone Index is calculated as the ratio of the sum of all expenditures below the m edian to the sum of all expenditures below the median when brought up to the median level (Garris & Cohen, 1996; Hickrod, Chaudhari, & Lundeen 1980; Hirth, 1994; Kearney & Chen, 1989; Oesch & Paquette, 1995; Thompson, Wo od, & Honeyman, 1994; Wood, Honeyman, & Bryers, 1990). It is used to assess equity in the di stribution of resources among students in the lower half of the spending distribution. It compar es the total amount spent for all students below the median student with a calculation of what would have to be sp ent to bring all of them up to the median revenue per student for the state. Th e closer this value is to 1, the less dispersion there is among students in low sp ending districts (Picus & Toenje s 1994). Another way of stating the index value/dispersion relationship would be to say that the higher the index, the more equitable the distribution. Hickrod, Chaudhari & Lundeen (1980) provided a clear explanation fo r the logic of the McLoone Index, stating that Eugene McLoone an d others argued that bringing up low spending districts should be the primary concern of the state, and that high spending districts should be allowed to move out in front as far as they want to go (p. 182) The McLoone Index has been used in numerous studies of per-pupil revenue and expenditure e quity, and its use continues in many present-day research studies (Brown, 1999; Fowler, Jr., 1996; Hirth, 1994; Johnson &

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62 Pillianayagam, 1991; Prince, 1997; Stark, Wood, & Honeyman, 1993; Stiefel, Rubinstein, & Berne, 1998; Verstegen, 1996; Yancey, 2002). Gini Coefficient and Lorenz Curve The Gini coefficient originated during the early 1920s out of an interest in measuring social inequality as a function of unequal dist ribution of wealth and incom es (Gini, 1921; Lows, 1984). It continues to be used toda y as well, very often in the analysis of income disparity, and can be used in the analysis of educational finance disparity. In studies of e ducational finance, it is used to analyze how a certain percentage of students will match up with a certain percentage of instructional expenditures (or re venues), by examining how far the distribution is from providing each percentage of students with an equal percentage of instru ctional expenditures or revenues (Hussar & Sonnenberg, 1999; Thompson, Wood, & Honeyman, 1994). Previous researchers have also applied the Gini coefficient to studies of equity in community college funding (Harrell, 1992; Br own, 1999; Yancey, 2002). Yancey, referencing Lows, credited G. Alan Hickrod as the chief pro ponent of the use of the Gini coefficient as a measure of inequity in public school finance, and cited Hickrods use of the Gini coefficient in a longitudinal study of Illinois public schools for the period 1972-1981 to test wealth neutrality (Lows, 1984 as cited in Yancey, 2002, p. 79). Wealth neutrality is the relationship between the school districts wealth and the per-pupil expend itures of the school dist rict (Hickrod, Chaudhari, & Lundeen, 1980). School district funding is considered wealth neutral if there is little or no relationship between the local dist rict wealth and the local dist rict expenditure per pupil. Lows (1984) contended that the Gini coefficient is a unique nu merical value which is used as an index of inequality. The coefficient index is calculated from a formula from which the resulting value ranges from between zero and one Hussar and Sonnenberg (1999) noted that, a Gini coefficient of zero means absolute equality and a value of one means absolute inequality.

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63 The Gini coefficient has a minimum value of zero, and increasing va lues mean increasing disparity (Hussar & Sonnenbe rg, 1999, p.15). Hussar and Sonnenberg also identified two advantages of the Gini coefficien t. First, it equally weights all students in the distribution as it measures the disparity in the distribution. Secondl y, it is clearly illustrate d by the Lorenz curve. The Gini coefficient has long been recognized as more easily interpreted when it is graphically illustrated by the Lorenz curv e (Berne & Stiefel, 1984; Bezeau, 1979; Hussar & Sonnenberg, 1999; Odden, 1992; Thompson, Wood, & Honeyman, 1994; Yancey, 2002). Lows (1984) described the Lorenz curve as a graphi cal representation of the distribution of the cumulative proportion of wealth (or income) a ssociated with the cumulative proportion of a population. In studies of school finance, the Lo renz curve is a graph formed by plotting the cumulative percentage of student enrollments agai nst the cumulative percentage of revenues or expenditures for those enrollments (Yancey, 2002). A straight, 45-degree line represents equal distribution and perfect equity; whereas a bow in the line repr esents unequal distribution and imperfect equity (Lows, 1984; Yancey, 2002). The Gini coefficient and Lorenz curve have been used in numerous studies of per-pupil revenue and expenditure equity, and their use cont inues in many present-day research studies of equity in school finance (Brown, 1999; Fowl er, Jr., 1996; Harrell, 1992; Hirth, 1994; Hussar & Sonnenberg, 1999; Johnson & Pillianayagam, 199 1; Prince, 1997; Stark, Wood, & Honeyman, 1993; Stiefel, Rubenstein, & Berne, 1998; Ve rstegen, 1996; Wood, Honeyman, & Bryers, 1990; Yancey, 2002). Weighted Versus Unweighted Dispersion Measures The use of weighted and unweighted pupils (in this study FTE student enrollm ent) is common practice in analyzing equity relationships in per-student re venue distributions. It is also addressed in fiscal equity literature. For fiscal equity analyses of Florida community colleges,

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64 degree completers and FTE student enrollment ar e weighted for certain analyses. The Florida Community System Performance Funding Report for 2007-2008 states the following: The mathematical process of weighting completers against a standard permits comparison and analysis of dissimilar programs on a level playing field. Because programs of instruction offered in the comm unity college system have lengths ranging from 9 credit hours to 88 credit hours, the first step in establishing a common basis for comparison is to calculate the cost per credit hour (or equivalent), which is then multiplied by the standard length of each progr am to establish the cost per completer each program. The annual cost analysis is used to calculate the st atewide average cost for an Associate of Arts (AA) degree which is 60 credit hours long. The AA degree cost per completer is used as the standard against which all other programs are weighted (The Florida Community System Performance Funding Report for 2007-2008, July 2007, p.47). Berne and Stiefel (1984) discuss the use of modifications in equity measures through weighting of unequal pupils. Berne and Stiefe l, however, address weighting modifications in the context of vertical equity. In particular, Berne and Stiefel states the following: If a decision can be made regarding the a ppropriate differences in objects that unequal groups of pupils should receive, then the di spersion measures used earlier to assess horizontal equity can be reformulated to incorporate the vertical-equity dimension. Because the horizontal-equity measures are basically dispersion measures, and since the reformulation consists of a weighting pro cedure, the reformulated horizontal-equity measures are referred to as weighted dispersion measures. The calculations of these weighted dispersion measures can be described as follows. First, for each different group of pupils identified for vertical-equity consider ations, a weight must be established that expresses the amount of the obj ect that the group of pupils should receive compared to a baseline group. After this weighting scheme is established, the number of pupils times their assigned weights is computed for each district (Berne and Stiefel, 1984, p.83). Berne and Stiefel (1984) go further in addres sing the differences and resulting debates about the appropriate use of weighted and non-weighted dispersion measures. They draw the conclusion provided below: The literature review presente d in chapter 5 showed clearl y that analyses of schoolfinance equity usually include an assessmen t of horizontal equity, often captured by unweighted dispersion measures such as the federal range ratio and the coefficient of variation. At the same time, critics of th e existing studies argue that unweighted dispersions measures are difficult to interpre t because the assumpti on that all pupils are equal is not met and that therefore, wei ghted dispersion measures should be employed

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65 (p.233). The weighted dispersion measures do not always show greater equity (lower dispersion) than the unweighted dispersion measures (p.238). Other authors have also addressed the concept of pupil weighting in fi scal equity studies and in literature. Thompson, Wood, Honeyman (1994) addresses pupil weighting in the contexts of vertical adjustments, vertical programs, and categorical aids as a co mmon alternative to pupil weighting (pp 235-236). Yancey (20 02) states the use of weighted FTE in his horizontal equity statistic measures, stating: Different program areas have differing costs and differing fee revenues. Consequently, equitable operating funds wound not be equal operating funds per un-weighted FTE (p.108). However, Yanceys Gini coefficient results (Tables 4-11 and 4-12, p. 129, suggests that unweighted FTE were used for the Gini coefficient tests. It is important to note that Berne and Stie fel discuss the reformatted horizontal equity measures when applied to vertical equity an alysis as weighted dispersion measures. For horizontal equity analyses, it can be seen that the use of we ighted versus un-weighted FTE students in analyses of the Gini coefficient measur e does appear to result in different values for the equity coefficient of the Gini dispersion meas ure. This is largely because the numerator of the Gini coefficient formula contains a multiplie r factor for the pupil objects in K-12 district analysis and FTE students in community college fiscal analysis. This difference is discussed more fully in chapters 4 and 5 of this study. Fiscal Equity in Florida Community Colleges As indicated in chapter 1, Brown (1999) and Ya ncey (2002) have previously studied fiscal equity in operating fund distri butions for Florida community co lleges. Browns research found funding distribution was more equitable in ye ar 1994-95 prior to the im plementation of performance funding than in 1996-97 than the fi rst year of full implementation in 1996-97 (Brown, 1999, p. 108). Yanceys research found th at of the six statisti cal measures, only the

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66 restricted range indicated a tre nd in equity that could be supp orted statistically as the 95% confidence level. That trend was a trend was an increasing restricted ra nge over time, indicating decreasing equity in the system (Yancey, 2002, p. 141). The results of these previous research studies are summarized below (Table 2-1). For this 2007 research study, perhaps the most significant insights on the status of fiscal equity in Florida community colleges are prov ided in the following public documents: those related to structural changes to the funding model aimed at e qualization; the current holdharmless from hurricane and compression/ equa lization funding policie s; Florida Community College Plan for the Social and Economic Future of the State, and; the 2007 Florida Legislative for addressing the states changing dem ographics. These are discussed below. The Florida Community College Funding Form ula Committee meets three to four times a year with formal work plans approved by th e Council of Presidents Policy and Advocacy Subcommittee. Formal meeting minutes are pro duced and are published on the Florida Division of Community Colleges Finance.org website. The Funding Formula Committee work plan for 2005-06 resulted in the adoption of nine recomme ndations for structural changes to the funding formula (Florida Community College System Funding Committee, January 19, 2005). The structural changes were aime d at improving standards and f unding equalization in the funding formula, and included the following: adjustments to instructional support categories and student faculty ratio parameters; changes for small colleges and colleges with rural campuses; adjustments to salary factors for Health pr ograms under PSV and PSAV instruction; and cost factors for serving disabled students. The equalization effects of these changes are referenced in the compression/equalization funding policy cited below.

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67 In addition to the structural changes adopted as listed above, formulation of the capacity restoration and compression/equalization funding policies began in 2005-2006 (Council of President Meeting Report, Marc h 2005; Council of President M eeting Report, October 2005). The capacity restoration funding policy was aime d at holding-harmless those colleges whose students and FTEs were adversely impacted by hurricanes in 2004. The March 2005 meeting report focuses on concerns about: the very disp arate impact of the hurricanes on enrollment and the need to meliorate the spread that creates the stress among the colleges (p.2). The meeting report includes a funding model simulati on chart indicating spread between the high % and low % of model funded per college. These spreads, which follows, formed the basis of the compression/equalization funding policy and subs equent legislative budget requests: 2004-2005, 21.66% spread; 2005-06, 18.66% spread; 2006-2007, 15% spread; 2007-08, 13.06% spread, and 2008-09, 10.54% spread. The simulation was based on the assumptions of constant enrollment, 1.5% inflation, 5% annual fee increases, and state support incr eases of $59,117,008 in 2005-06 and $50 million thereafter (p.10). The October 2005 meeting report include s focuses on capacity building and compression/equalization (p. 3). The compre ssion/equalization polic y reads as follows: The Community College System has recognized a disparity in funding institutions based on the funding ge nerated by the Funding Model. Te range as a percent of the funding formula standards is currently approximately 20 percentage points. A target range level of equalization would be approximately 5 percent. A certain amount of equalization/ compression will occur naturally as funding is distributed based on the Funding Model. However, the process would be accelerated by providing targeted funds for the sole purpose of providing additional funds to the most under-funded institutions. The themes of compression/equali zation as well as that of soci al and economic equity is carried forward to the Florida Community Colleg es Council of Presidents Plan for Floridas

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68 Community College System And the Social an d Economic Future of the State, August 2007. This plan reads in part as follows: To develop the necessary opportunities, it is pr oposed that community college funding be increased $100 million per year for 10 years. The funding should be derived from state general revenue and not tuition increases. A new, dedicated source of funding should be chosen to stabilize fluctuating PECO. Perfor mance measures would ensure accountability for resources allocated to community colle ges. A statement added to the Florida Constitution would assure all state citizens access to quality, affordable community college education as a fundamental right. The Council of Presidents Plan for Flor idas Community College System goes on to recognize the changing demographics in Florida, and the need to better address minority education: In addition to their multiple responsibilities, community colleges serve the large majority of students in Florida higher education, and those students are incr easingly diverse and place bound. There are 850,000-900,000 community college students in Florida. Among them are the largest percentages of Hispan ic and African Americans at a time when Spanish is the first language spoken in se venteen percent (17 %) of Florida homes. I conclude this section on equity in Florid a community colleges with the mandate from the Florida House of Representatives, 2007 Legislat ure, Enrolled CS/HB 717 4, Engrossed 3. Section (1) reads as follows: The Office of Economic and Demographic Research shall conduct a study of the higher education enrollment forecasting models currently in use in the state. The study must analyze the current models and provide options for improvements. The review shall sp ecifically examine ways to include Floridas changing demographics in the forecasts. A final report with recommendations shall be submitted to the President of the Senate and the Speaker of the House of Representatives by February 1, 2008 (p.2). Summary This chapter presented the results of the li terature review for this study. The results indicate th at drastic changes in demographics in America and in Florida are of serious concern, and that the call for performa nce accountability includes a call for serving currently underrepresented populations in higher education. The literature results also indicate that previous

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69 research studies found declining equity in Flor ida community college funding distributions, and there is continuing concerns on the part of Florida community college policymakers and administrators about inequity in the current funding distributions, as well as about ways to address Floridas changing demographics in the forecasting and funding m odels. Therefore, it seems appropriate to continue to examine equity in the distribution of the systems operating funds, and to explore ways to improve equity with performance funding included. Chapter 3 will describe the research methodology for such a study. Table 2-1. Summary of prev ious research findings Brow n (1999) and Yancey (2002). Horizontal Brown Yancey Equity Measure Years: 1994-95 1996-97 Years 1996-97 2000-01 Range Decreasing Equity (p. 83) Not Informative (p. 145) Restricted Range Decreasing Equity (p. 84) Not Informative (p. 145) Federal Range Ratio Decreasing Equity (p. 85) Not Informative (p. 145) Coefficient of Variation Decreasing Equity (p. 87) McLoone Index Decreasing Equity (p. 88) Gini Coefficient Decreasing Equity ( p. 89) Decreasing last 3 Years (p. 146)

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70 CHAPTER 3 RESEARCH METHODOLOGY This chapter explains the research me thodology used in this study. The research purpose, problem, design, raw data, and data analys is methods are described and explained. Purposes of the Study The purposes of this study were to examin e f iscal equity in the Florida Community College System (FCCS) during the five-year period of 2001-02 through 2005-06 and to explore possible improvement methods. Previous research studies by Yancey (2002) and Brown (1999) had found inequity in the per-student FTE re venue distributions to the 28 colleges. In the Brown study of years 1994-1995 and 199697, equity without performance funding in 1994-1995 was found to be better than equity with performance funding included in 1996-97. In the Yancey study of years 1995-96 through 2000-01, equity in per-student FTE revenue distributions were again found to be more equ ity when performance funding is excluded, than with performance funding included. Therefore, the first purpose of this 2007 study was to discern if equity with performance included has continue d to be less than when performance funding is excluded for the five-year period 2001-02 through 2005-06. The second purpose of this study is to explore adjustments to perf ormance funding that might lead to improved equity when performance funds are included in other operating revenues to the colleges. In particular, the second pur pose is to explore the effects of indexing performance funds appropriated to the colleges for the purposes of incentivizing and rewarding them for degree completers among Black Males and Hispanics. In the Florida, measure II performance funds are allocated to the colleges for this purpose. The effects of indexing measure II funds to the relative proportion of those popul ations in each colleges service area are explored.

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71 Research Problem As indicated, the Spellings Commis sion Report poi nts out that the U.S. workforce is in the midst of a sweeping demographic transformation. From 1980 to 2020, the white working-age population is projected to declin e from 82% to 63%. The minority portion of the workforce is projected to double from 18% to 37%, and the Hispanic/Latino por tion is projected to almost triple from 6% to 17%. The greatest increase in population growth in the U.S. workforce is occurring among those racial/ethnic groups with the lowest level of education, while the group reaching retirement age is predominantly white with higher levels of education. Demographic transformation is also occurring in Florida. The University of Florida Bureau of Business and Economic Research Report #148 indicates that th e non-Hispanic Black population in Florida will grow to be 16% of to tal and Hispanic population to 25% of total by year 2020. The Florida legislature has recognized the implications of this transformation to Floridas higher education systems, and recently asked colleges and universities to study how the rate of graduation for minorities might be improved (Legislative Mandate) Research Questions Research question one centers on discerning whether horizon tal fiscal equity in per-student FTE funding distributions to th e colleges improved, worsened, or remained unchanged over the five years of the study. The second research ques tion explores one method of possibly increasing fiscal equity in funding distributions when performance funds are included. (1) What influence did performance-based funding have in the changes in horizontal equity in the distribution of operating funds for Fl oridas 28 public community colleges for the years 2001-02 through 2005-06? (2) What effects will indexing the appropriations of applicable performance funds to the proportions of selected speci al population groups Black Males and Hispanics have on

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72 horizontal equity in the dist ribution of operating funds for Floridas 28 public community colleges for the years 2001-02 through 2005-06? Research Design This study is non-experime ntal for research question one, and ex-post facto correlational for research question two (Shavelson, 1996). Fo r question one, the framework identified by Berne and Stiefel (1984) for evaluating equity in public school systems will be used to establish the sum of student fees and state support ope rating funding as the independent variable. Perstudent revenue is the dependent va riable of equity for students in this study. Statistical analysis, including descriptive statistics, horizontal equity statistics measures, and analysis of variance (ANOVA) will be used to discer n whether equity in per-studen t revenue distributions with performance included and with performance excluded increased, decreased, or remained unchanged. For question number two, descriptive statistics horizontal equity statistic measures, and analysis of variance (ANOVA) will be used to di scern whether equity in per-student revenue distributions with special demographics popul ation adjusted (SPDA) performance included increased, decreased, or remained unchanged when compared to equity in per-student revenue distributions with non-SPDA-performance included. Correlational statisti cal analysis will be used to measure the strength of relationship between distributions with SPDA-performance included and the populations of Black males and Hispanics in the respective college service areas. By convention, the research design for question two is a type of ex post facto correlational design (Hutchinson, 2004; Shavelson, 1996 p. 26). Population of the Study Population data was obtained from t wo s ources. To answer question one, operating revenue data was obtained from the Florida De partment of Education, Division of Community

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73 Colleges (Appendix A). The operating revenue data, inclus ive of performance funds, comprises the revenue distributions per full-time equivale nt (FTE) student to the 28 public community colleges in Florida for the five fiscal year s of 2001-02 through 2005-06. The operating revenue data also included the non-weighted FTEs for each college for each year. To answer question two, demographics data for 2001 -2006 and projections for 2010 were obtained from the University of Florida Bu reau of Economic and Business Research (Appendix B). The demographics data, based on the 2000 U.S. Census data, provide population projections by age, sex, race, and Hispanic origin for Florida and its counties Population projections by age, sex, race, and Hispanic origin fo r Florida and its counties, 2006-2030 were also obtained (Florida Population Studies, Volume 40, Bulletin 148, June 2007). In addition, data for performance indicator outputs, outcomes, and degree program completers was obtained from the Florida Department of Education, Di vision of Community Colleges for years 2001-02 through 2005-06. The performance outputs, outcomes, and degree program completers da ta provided the Black male and Hispanic completers and measure II performance funding for each college and each year of the study. Data Analysis To answer question one, academ ic program-cost-weighted FTEs for each college were divided into the colleges tota l operating funds to calculate pr ogram-cost-weighted per-student revenue. Two separate per-student-revenue values were calculated for each college each year: one with performance funding included, and one with performance funding excluded. This resulted in two separate per-st udent revenue distributions for ea ch college and each year of he study; one with performance included, the othe r with performance funds excluded. The academic program-cost-weighted FTE values were calculated by indexing the non-weighted FTEs for each college to the five-year average FTEs of each colleges lowest cost academic program: adult

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74 education. A FCCS-system average cost per progr am was also calculated. Costs and FTEs for each academic program for each college are provided in the Division of Community College Cost Analysis Report. A Cost Analysis Report fo r each fiscal year is produced and published by the Division of Co mmunity College. The six horizontal equity statistic measures were calculated using the two academicprogram cost-weighted per-student revenue distributions; with performance funding included, and with performance funding excluded. Provided belo w are definitions of the six equity statistic measures, method of interpreting their results and formulas for their calculations. For each statistics measure, descriptive statistics were r un to examine means, standard deviation, median, skewness and kurtosis. Regression statistics were run to examine slopes. Range The range statistic is calculated by simply subtracting the lowest per-FTE student cost value from the highest per-FTE student value. Therefore, RANGE = Highe st Xi Lowest Xi where Xi was the per-FTE student cost for the institution for a particular year. The smaller the value of the range, the bette r is horizontal equity (T hompson, Wood, & Honeyman, 1994; Verstegen, 1996; Verstegen & Salmon, 1989). The ra nge was calculated for each year with and without performance funding. Restricted Range The restricted range was calculated as the di fference between the observ ation at the 95th percentile and the 5th pe rcentile. The highest observations (beyond the 95th percentile) and the lowest observations (below the 5th percentil e) were disregarded. Accordingly, RRANGE = Highest95th% Lowest5th%. Again, the smaller the restricted range of the distribution, the greater is the equity. The restricted range was calculated for each year with and without performance funding.

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75 Federal Range Ratio The federal range ratio is calculated by divi ding the restricted ra nge by the revenue per pupil per district at the 5th percentile (Thompson, Wood, & Honeym an, 1994, p. 248). By expressing essentially the same information as th e restricted range statis tic only in terms of a ratio, the federal range ratio ove rcomes the inflation problem and, consequently, is a "more acceptable statistic than range or restricted ra nge" (Hirth, 1994, p. 174). The smaller the decimal calculated for the federal range ra tio, the more equitable the dist ribution. The federal range ratio was calculated by dividing the restricted range by the revenue per pupil per district at the 5th percentile for each year with and without performance funding. Coefficient of Variation The coefficient of variation (C.V.) was calcula ted by dividing the standard deviation of the distribution by the mean of the distribution (Thompson, W ood, & Honeyman, 1994). The mean revenue per FTE student y was obtained by taking the sum of all the colleges' available funds and dividing it by the total weighted FTE in th e system. The formula for the mean revenue per FTE student y is noted below: 1 1 n ii i n i ier y e where ei = number of students for each college ri = per-student revenue for each college and N = number of colleges in the system The coefficient of variation (C.V.) formula is: 2()iieyy E CV y where ei = number of FTE students for each college E = total FTE for all colleges

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76 The coefficient of variation will be calculated on per-student revenue for each year of the study with and without performance funding included. McLoone Index The McLoone Index was calculated as the rati o of the sum of all expenditures below the median to the sum of all expenditures below the median when brought up to the median level (Garris & Cohen, 1996; Hickrod, Chaudhari, & Lundeen, 1980; Hirth, 1994; Kearney & Chen, 1989; Oesch & Paquette, 1995; Thompson, Wo od, & Honeyman, 1994; Wood, Honeyman, & Bryers, 1990). It is used to assess equity in the distribution of resources among students in the lower half of the spending distribution. It compar es the total amount spent for all students below the median student with a calculation of what would have to be sp ent to bring all of them up to the median revenue per student for the state. The closer the value is to 1, the less dispersion there is among students in low-spending districts (Pic us & Toenjes 1994). Another way of stating the index value / dispersion relations hip would be the higher the index, the more equitable the distribution. Expressed as a formula, the McLoone index is, 1 1*iN ii i N ier MI M e where ei = number of students (FTE) for each college ri = per-student revenue for each college 1 N ii ier = total revenue of colleges below the median N = number of colleges whose per-student revenue were below the median. S = number of students (FTE) in each college whose revenue was below the median. and M = median per-student revenue. The McLoone index was calculated for each ye ar with and without performance funding.

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77 Gini Coefficient and Lorenz Curve The coefficient index is calcu lated from a for mula which yi elds resulting value ranges between zero and one. Hussar and Sonnenberg (1 999) noted that, a Gini coefficient of zero means absolute equality and a value of one means absolute inequality. The Gini coefficient has a minimum value of zero, and increasing va lues mean increasing disparity (p.15). The formula used for the Gini coefficient is Gini Coefficient = 22ij iij ij i X X PPP where i j is the summation of all institutions i, j from i = 1 to N and from j = 1 to N N = the number of institutions in the system Pi = the student FTE for institution i Pj = the student FTE for institution j = population mean per-student expense or revenue value Xi = per-student cost or revenue for institution i and Xj = per-student cost or revenue for institution j. The Gini coefficient was calculated for each ye ar with and without performance funding. A Lorenz curve was used to graphically depict the Gini coefficient. The Lorenz curve is a cumulative frequency curve that compares two se ts of data; in this study cumulative % of perstudent revenue to corresponding cumulative % of FTEs. Lorenz curves demonstrate the degree of concentration or inequality of a variable, such as the inequality of income, the concentration of ethnic minorities, etc. In this study, the Lorenz curve is used to depict the inequality of revenue distribution rela tive to FTE students. To answer question two, demographics data for years 2001-2006 and projections for 2010 were obtained from the University of Flor ida Bureau of Economic and Business Research The counties served by each Florida community college (Table 3-1) were obtained from the Florida Department of Education Report for the Florid a Community College System: The Fact Book,

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78 February 2006. Populations for college-age Black males (Table 3-2) and male and female Hispanics (Table 3-2) in each of the college serv ice areas were totaled for each year of the study. A special-demographics population adjustme nt (SPDA) index was calculated by the researcher using the special popula tions in Tables 3-2 and 3-3 and the numbers of Black male and English as Second Language (ESL) and (ENS) degree program completers for performance Measure II ( Table 4-32). The SPDA-indexes (Table 4-33) were calculated for each ethnic group by dividing each colleges ethnic completers by its respective ethnic population. This yielded a special population served percenta ge. The special population served percentage was then used to calculate an SPDA-index for each college for Black males and Hispanics for each year by dividing each colleges population served percentage by the lowest percentage served that year. The SPDA-index was then used to re-distribute the measure II performance funding for that year (Tables 4-34, 4-35, 4-36). The six horizontal equity statistic measures were calculated using the academic-program cost-weighted per-student re venue distributions; with SPDA-performance funding included. Horizontal fiscal equity was again tested and examined For each statistics measure, descriptive statistics were run to exam ine means, standard deviation, median, skewness and kurtosis. Regression statisti cs were run to examine slopes. Co rrelational statistical analysis was used to examine the strength of relations hip between special population in each colleges service area to performance funding be fore and after SPDA-adjustments. Summary This chapter presented the research purposes, problem, questions, designs and data analysis methods used for this study. Chapter 4 will present the results of the data analysis.

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79 Table 3-1. Florida counties by community college serving areas. Colleges Florida Counties In Service Areas Brevard Brevard County Broward Broward County Central Florida Marion, Citrus, Levy Counties Chipola Jackson, Calhoun, Ho lmes, Liberty, Washington Counties Daytona Beach Volusia, Flagler Counties Edison Lee, Charlotte, Collier, Glades, Hendry Counties Fla. CC@Jax Duval, Nassau Counties Florida Keys Monroe County Gulf Coast Bay, Franklin, Gulf Counties Hillsborough Hillsborough County Indian River St. Lucie, Indian River, Martin, Okeechobee Counties Lake City Columbia, Baker, Dixie, Gilchrist, Union Counties Lake-Sumter Lake, Sumter Counties Manatee Manatee, Sarasota Counties Miami Dade Dade County North Florida Madison, Hamilton, Jeff erson, Lafayette, Suwa nnee, Taylor Counties Okaloosa-Walton Okaloosa, Walton Counties Palm Beach Palm Beach County Pasco-Hernando Pasco, Hernando Counties Pensacola Escambia, Santa Rosa Counties Polk Polk Counties Saint Johns River Putnam, Clay, St. Johns Counties Saint Petersburg Pinellas County Santa Fe Alachua, Bradford Counties Seminole Seminole County South Florida Highlands, DeSoto, Hardee Counties Tallahassee Leon, Gadsden, Wakulla Counties Valencia Orange, Osceola Counties Source: Florida Department of Educati on, The FACT BOOK, Report for The Florida Community College System, February 2006, p11.

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80 Table 3-2. College-age black males in the community college service areas for years 2002, 2003, 2004, 2005, and 2006. Colleges 20022003200420052006 B revar d 12 461 12 222 12 785 13 654 14 119 B rowar d 109 718 108 918 114 899 120 209 123 953 C entra l Fl or ida 10 325 10 284 10 690 11 279 11 744 Chi po l a 9 049 9 152 9 382 9 782 10 192 D aytona B eac h 14 295 13 973 15 039 16 352 16 852 Edi son 18 445 17 537 18 902 20 033 21 247 Fl a. CC@J ax 66 549 67 153 70 661 74 565 77 067 Fl or id a K eys 1 415 1 313 1 329 1 404 1 379 G u lf C oast 7 183 7 032 7 384 7 669 8 109 Hill s b oroug h 48 017 46 583 49 344 52 550 54 857 I n di an Ri ve r 15 682 15 305 16 277 17 245 18 366 L a k e Ci ty 8 660 8 675 8 696 8 872 9 116 L a k eS umte r 9 046 9 217 9 781 10 343 10 710 M anatee 10 731 10 466 10 955 11 393 11 725 Mi am i D a d e 145 375 133 259 134 237 137 493 137 842 N ort h Fl or ida 10 056 10 151 10 536 10 847 10 890 Ok a l oosaW a l ton 6 786 6 850 7 046 7 475 7 619 P a l m B eac h 52 410 52 294 53 802 57 092 59 009 P ascoH ernan d o 3 919 3 809 4 236 4 803 5 204 P ensaco la 21 042 21 315 21 498 21 402 22 017 P o lk 19 835 19 766 20 701 21 641 22 791 S anta F e 16 632 17 122 17 729 18 749 19 109 S em i no l e 11 997 11 479 12 236 12 982 13 548 S out h Fl or ida 5 403 5 171 5 384 5 466 5 459 S t. J o h ns Ri ve r 8 707 8 744 9 417 9 929 10 341 S t. P eters b urg 25 088 24 611 26 113 27 484 28 179 T a ll a h assee 31 348 32 076 34 047 36 091 36 975 V a l enc ia 62 702 60 727 64 873 69 005 72 804 Totals:762,876745,204777,979815,809841,223 Source: University of Florida, Bureau of Economic & Business Research, Special Order Population Data 2002-2006 and 2010 ARSHO C ounty Spreadsheet, September 4, 2007.

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81 Table 3-3. College-age male and female Hispanics in the community college service areas for years 2002, 2003, 2004, 2005, and 2006. Colleges 20022003200420052006 B revar d 12 891 14 772 17 912 19 104 21 070 B rowar d 186 707 198 604 212 178 223 753 236 464 C entra l Fl or ida 11 389 13 296 15 539 17 725 19 870 Chi po l a 2 340 2 485 2 382 2 750 2 919 D aytona B eac h 19 500 22 245 25 924 28 511 31 505 Edi son 71 494 82 402 98 585 109 056 119 365 Fl a. CC@J ax 20 517 23 938 28 802 31 337 35 648 Fl or id a K eys 8 029 8 441 9 241 9 930 9 704 G u lf C oast 2 551 3 002 3 292 3 946 4 561 Hill s b oroug h 113 967 124 065 138 596 146 330 156 757 I n di an Ri ve r 23 660 27 335 32 101 35 987 39 872 L a k e Ci ty 2 135 2 339 2 525 2 788 3 006 L a k eS umte r 9 813 12 077 15 207 18 013 20 149 M anatee 23 864 27 590 33 180 36 594 40 239 Mi am i D a d e 865 594 886 024 903 277 932 029 948 686 N ort h Fl or ida 3 074 3 502 4 045 4 484 4 947 Ok a l oosaW a l ton 4 998 5 834 6 861 7 605 8 709 P a l m B eac h 96 460 103 281 114 069 118 782 125 003 P ascoH ernan d o 14 914 17 645 21 489 24 143 27 112 P ensaco l a 7 029 7 719 8 291 8 874 9 971 P o lk 26 837 31 510 37 872 41 962 47 629 S anta F e 18 298 10 687 12 220 13 754 14 638 S em i no l e 7 801 29 727 33 861 36 060 38 529 S out h Fl or ida 26 906 19 154 20 900 21 130 21 804 S t. J o h ns Ri ve r 9 500 9 016 10 672 11 618 13 153 S t. P eters b urg 27 027 29 433 32 799 35 591 37 660 T a ll a h assee 8 373 9 277 10 425 11 581 12 248 V a l enc i a 151 177 169 576 196 812 209 306 230 532 Totals:1,776,8421,894,9762,049,0572,162,7432,281,750 Source: University of Florida, Bureau of Economic & Business Research, Special Order Population Data 2002-2006 and 2010 ARSHO C ounty Spreadsheet, September 4, 2007.

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82 CHAPTER 4 DATA ANALYSIS AND RESULTS In this chapter the d ata a nalysis process and results will be presented as described in Chapter three. A brief review of raw data, the statistics measures of horizontal fiscal equity in public school systems, and adjust ment calculations performed by th e researcher are provided. Each research question will be analyzed and answered with results given in order. Chapter Five will provide a discussion of observations, areas of possible further research, implications for college administrators, and overall summary. Raw Data, Data Calculatio ns, Statistics Measures Raw data for State support funding, student fees and full-time-e quivalent (FTE) was obtained from the Florida Department of E ducation for the five years 2001-02, 2002-03, 200304, 2004-05 and 2005-06. State support is comprised of General Revenue Community College Program Funds (CCPF), Lottery CCPF, Perfor mance Based Budget (PBB) funding. State support for each year added with student fees comprises Total Funds Available in the study. Academic-program-cost-weighted FTEs were calculated by the researcher based on each colleges FTEs per academic program and indexed to the lowest cost academic program costs of adult education. Literature on weighted versus unweighted is gi ven in Chapter two. Details on the weighted FTE methodology, including a small colle ge factor, are given in Chapters three. The program costs and FTEs per program were obtained from annual Co st Analysis Reports obtained from the Division of Community Colleges. Total Available Funding for each college was divided by the colleges weighted FTEs with performance funding included and exclude d. The six statistics measures of Range, Restricted Range, Federal Range Ratio, Coeffici ent of Variation, McLoone Index, and Gini coefficient were used to examine the influe nce of performance funding on horizontal equity

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83 among the colleges for the five years of the st udy. In addition, non-program-cost weighted funding distributions were examined for the Gini coefficient in order to compare results to previous horizontal equity research. For each statis tics measure, descriptive statistics were run to examine means, standard deviation, median, sk ewness and kurtosis. Regression statistics were run to examine slopes. Research Question One Research question one centered on discerning whether horizontal fiscal equity in perstudent FTE funding distributions to the colleges improved, worsened, or remained unchanged over the five years of the study. (1) What influence did performance-based funding have in the changes in horizontal equity in the distribution of operating funds for Fl oridas 28 public community colleges for the years 2001-02 through 2005-06? Range Performance Included The range statistic for measuring horizontal equity in per-student funding is calculated by subtracting the lowest per-student FTE revenue value from the highest value per per-student FTE revenue in the distribution for each year. The smalle r the range value, the gr eater is the equity in the distribution. The Range statistic with performance fundi ng included decreased for the two years of 2002-03 and 2002-04 from the highest level in 20 01-02 indicating increa sing equity in the distribution for that period (Table 4-7). Howe ver, the range began increasing in 2004-05 and continued in 2005-06 indicating a re versal in the previous years increasing equity towards a trend of decreasing equity. The decrease in equity in 2004-05 was driven in part by a $119 increase in low value but more largely by a $558 in crease in the high value; indicating a greater increase in per-student revenue at the higher percentile. Similarl y, the decrease in equity in 200506 were driven in part by a $188 increase in low value but more largely by a $572 increase in the

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84 high value. Overall, equity as measured by the range statistic with pe rformance funding included increased two years and decreased two years (Figure 4-7). The skewness of the distribution performance fu nding included is slightly positive for year 2001-02 (0.21) but moved to slightly negative (0.107 to -0.118) for the remaining years 2002-03 through 2005-06. This indicates mo re outlier per-student FTE revenue values at the lower end of the distribution (Table 4-1). The slope of the predicted range with pe rformance funding included shows a positive trend over the 2002-2006 years of the study (Figure 4-1). This positive slope at 24.72 indicates a general movement away from funding equity over the 2002-2006 years of the study. The ANOVA regression resu lted in F = 0.597, and a signi ficant regression equation was not found (F(1,4) = 0.82, p<.05), significant F = 0.597. Range Performance Excluded The Range statistic with performance fundi ng excluded decreased for the two years of 2002-03 and 2002-04 from the highest level in 20 01-02 indicating increa sing equity in the distribution for that period (Table 4-8). The range decrease in 2002-03 was driven by a noticeable $570 in the highest value for the year The range in the dist ribution reversed for 200405 and 2005-06 indicating decreasing equity the last two years. The decrease for the last two years were driven by large increases in the highest values; $547 a nd $430 respectively, and reflects a similar trend as for the range with performance included (Table 4-7). Also, as in Table 4-7, the decrease in equity in 2004-05 was driven in part by a $119 increase in low value but more largely by a $547 increase in the high value; indicating large increases in per-student revenue at the highest values of the distribution. Similarly, the d ecrease in equity in 2005-06 was driven in part by a $167 increase in low value but more largely by a $430 increase in the high value. Overall, equity as measured by the ra nge statistic with perf ormance funding excluded increased two years and decreased two years (Table 4-8).

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85 The skewness of the distribution with performance funding excluded is slightly positive for year 2001-02 (0.22) but moved to slightly ne gative (-0.102 to -0.108) for the remaining years 2002-03 through 2005-06. This indicates more outli er per-student FTE re venue values at the lower end of the distribution (Table 4-3 ). The slope trend line of Predicted Range with Performance excluded shows a very small increase over the 2002-2006 years of the study (Figure 4-2). This positive slope at 18.18 indicates a general movement away from funding equity over the 2002-2006 years of the study. The ANOVA regression resulted in F = 0.033, and a significant regres sion equation was not found (F(1,3) = 0.033, p<.05), significant F = 0.866. It is also important to note that the range statistic with performance funding excluded were smaller for each year in the study than the range statistic with performance funding included; indicating that, when usi ng the range statistic, equity is greater in the distribution when performance funding is excluded. Restricted Range Performance Included The Restricted Range statistic for measuring horizontal equity in per-student funding is calculated by (a) excluding the per-student FTE revenue values at or below the 5th percentile and at or above the 95th percentile, and (b) subtracting the re maining lowest per-student FTE revenue value from the highest remaining value per per-s tudent FTE revenue in the distribution for each year. The smaller the restricted range value, the greater is the equity in the distribution. The Restricted Range statistic with perfor mance funding included decreased for the year 2002-03 from the previous year higher level in 2001-02 indicating increasing equity in the distribution for that period (Table 4-9). The restricted range increa sed each of the next three years 2003-04, 2004-05, and 2005-06; indicating decr easing equity in the distribution. The increases over the three years were driven la rgely by small increases and a reduction in the lowest values each year, and by larger increases in the highest values each year. This indicates

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86 that colleges in the already higher percentile s of per-student FTE revenue were gaining additional per-student FTE revenue. These gains in per-student FTE revenue for colleges already in higher percentiles confirm results previously found for the range with performance included (Table 4-7). Overall, equity as measured by the rest ricted range statistic with performance funding included decreased one year a nd increased the last three years (Table 4-9). The slope of predicted restri cted range with performance included shows an increasing trend over the 2002-2006 years of the study (Figure 4-3). This positive slope at 176.02 indicates a move away from funding equity over th e 2002-2006 years of the study. The ANOVA regression resulted in F = 11.02, and a significa nt regression equation was found (F(1,3) = 0.521, p<.05), significant F = 11.02. Restricted Range Performance Excluded The Restricted Range statistic with perfor mance funding excluded decreased for the year of 2002-03 from the higher level in 2001-02. This decrease indicates increasing equity in the distribution for that period (Table 4-10). The de crease in restricted ra nge with performance excluded and corresponding increase in equity for 2002-03 was driven by small decreases ($39 and $61, respectively) in the lowest and highest values. Equity reversed the following year 2003-04 when the restricted range with perfor mance excluded increased $278 per-student FTE revenue; driven by a decrease in the lowest value but an increase in the highest for the year. The largest decrease in restricted range with performance excluded and corresponding largest increase in equity occurred in 2004-05. This la rge equity increase was dr iven by large increases ($800, $471 respectively) in both the lowest and hi ghest values; resulting in a large decrease in the restricted range with performance excluded. Equity reversed again in 2005-06 to a decrease driven by a greater than two-tim es increase in the highest valu e compared to the lowest; $180 and $459, respectively. These swings back and fort h indicate that colleges at both the lowest and

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87 highest per-student FTE revenue spectrum were gaining additional per-student FTE revenue funding. Overall, equity as measured by the rest ricted range statistic with performance funding excluded increased two years and decr eased two years (Table 4-10). The slope of predicted restrict ed range with performance fund ing excluded is positive over the 2002-2006 years of the study; indicating decr easing equity even when performance is excluded (Figure 4-4). This positiv e slope at 28.70 indicates a move away from funding equity over the 2002-2006 years of the study. The AN OVA regression resulted in F = 0.521, and a significant regression equation was not found (F(1,3) = 0.521, p<.05), significant F = .522. It is important to note that the restri cted range statistic with perf ormance funding excluded were smaller for three of the years in the study than the restricted range sta tistic with performance funding included. Federal Range Ratio Performance Included The federal range ratio statistic is calculated as the restricted range statistic divided by the per-student FTE revenue at or be low the 5th percentile. The smaller the value of the federal range ratio, the greater is the equity in the distribution. The federal range ratio statistic with perfor mance funding included decreased for the year 2002-03 from the previous year higher level in 2001-02 indicating increasing equity in the distribution for that period (Table 4-11). The Fe deral ratio statistic incr eased each of the next three years 2003-04, 2004-05, and 2005-06; indica ting decreasing equity in the distribution. Overall, horizontal fiscal equity as measured by the federal range ratio statistic with performance funding-included decreased one year and increas ed the last three years (Table 4-11). The skewness of the federal range distributi on with performance funding included is the same as for the restricted range with performan ce included (Table 4-2): negative for each year of the study (-0.050 to -0.145) indicating more outlier per-student FTE revenue values at the lower

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88 end of the distribution. The slope of the fede ral range ratio with pe rformance-funding included shows a positive trend over the 2002-2006 years of the study (Figure 4-5). This positive slope at 0.045 indicates a general movement away from funding equity over the 2002-2006 years of the study when measuring with the federal range ra tio with performance-funding included. The ANOVA regression resulted in F = 8.44, and a significant regression equation was not found (F(1,4) = 8.44, p<.05), significant F = 0.062. Federal Range Ratio Performance Excluded The federal range ratio statistic with perfor mance funding excluded decreased for the year of 2002-03 from the higher level in 2001-02. This decrease indicates increasing equity in the distribution for that period (Table 4-12). The equity increase in 200203 reversed in 2003-04 towards a sizeable move of inequity when the ratio increased from 0.86356 up to 0.94598. Equity increased again in 2004-05 with sizeable decrease in the ratio from 0.94598 down to 0.78747, and ended the study period with a swin g back towards a loss of equity in the distribution. As with the restri cted range statistic (Table 4-10), these swings back and forth in the federal range ration indicate that colleges at the lower pe r-student FTE revenue spectrum were gaining additional per-student FTE revenue funding. Overall, horizontal equity as measured by the federal range ratio statistic with perf ormance funding excluded increased two years and decreased two years (Table 4-12). The slope of predicted federal range ratio wi th performance funding excluded is slightly negative over the 2002-2006 years of the study; indicati ng increasing equity when performance is excluded (Figure 4-6). This negative slope at 0.005 indicate s a general move towards funding equity over the 2002-2006 years of the study when measuring with the federal range ratio with performance-funding included. The ANOVA regre ssion resulted in F = 0.104, and a significant regression equation was not found (F(1 ,3) = 0.104, p<.05), significant F = 0.76. It is important to

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89 note again that the federal range ratio statisti c with performance funding excluded were smaller for four of the years in the study than the fede ral range ratio statistic with performance funding included. Coefficient of Variation Performance Included Thompson, Wood, and Honeyman (1994) define d the coefficient of variation as the standard deviation divided by the mean, or the sq uare root of the variance divided by the mean. The formula yields a value between zero and one wherein smaller values demonstrate smaller variations in the distribution and greater equity. The coefficient of variation (C.V.)with pe rformance funding included decreased for the year 2002-03 from the previous year higher leve l in 2001-02 indicating incr easing equity in the distribution for that period (Table 4-13). The C.V. statistic increased in 2003-04 indicating decreasing equity, reversed in 2004-05 back to increased equity. The st atistic reversed upward again in 2005-06 indicating decreasing equity in the distribution in the last year of the study. Overall, horizontal fiscal equity as measured by the C.V. statistic with performance funding included decreased two years and increased two years (Table 4-13). The skewness of the distribution is positive in 2001-02 and negative the remaining years indicating outliers at the lower end of the per-stu dent FTE revenue in the distribution. The slope of the predicted C.V. with performance fundi ng included shows a positive trend over the 20022006 years of the study (Figure 4-7). This positive slope at 0.00022, indicating a general movement away from funding equi ty over the 2002-2006 years of the study, is very small. The ANOVA regression resulted in F = 0.040, and a significant regression equation was not found (F(1,3) = 0.026, p<.05), significant F = 0.881.

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90 Coefficient of Variation Performance Excluded The coefficient of variation (C.V.) with performance funding excluded decreased for the year 2002-03 from the previous year higher leve l in 2001-02 indicating incr easing equity in the distribution for that period (Table 4-14). The C.V. statistic increased in 2003-04 indicating decreasing equity, reversed in 2004-05 back to increased equity. The st atistic reversed upward again in 2005-06 indicating decreasing equity in the distribution in the last year of the study. This is a similar pattern to the C.V. with pe rformance included by the values each year with performance excluded are slightly higher. The skewness of the distri bution is also similar to C.V. with performance included pos itive in 2001-02 and negative the remaining years indicating outliers at the lower end of the per-student FTE re venue in the dist ribution. Overall, horizontal fiscal equity as measured by the C.V. statisti c with performance funding excluded decreased two years and increased two years (Table 4-14). The slope of the predicted C.V. with performance funding excluded shows a positive trend over the 2002-2006 years of the study (Figure 4-8). This positive slope at 0.00028, indicating a general movement aw ay from funding equity over the 2002-2006 years of the study, is very small. The ANOVA regression resulted in F = 0.040, and a significant regression equation was not found (F(1,3) = 0.040, p<.05), significant F = 0.852. McLoone Index Performance Included Thompson, Wood, and Honeyman (1994) define d the McLoone Index as the ratio of the sum of observations below the median to the sum of all observations that w ould be required if all observations below the median were brought up to the median level. The formula yields a value usually between zero and one wherein the larger th e value of the McLoone Index, the greater is equity of the lower half of the distribution.

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91 The McLoone index with performance funding included decreased for each of the years in the study; from a high of 0.784043 in 2001-02 to a low of 0.757718 in 2005-06 (Table 4-15); indicating declining equity for the colleges in the lower half of the per-student FTE revenue distribution. The skewness of the distribution, same as for the C.V., is positive in 2001-02 and negative the remaining years indicating outliers at the lower end of the per-student FTE revenue in the distribution. The slope of the pred icted McLoone index with performance funding included shows a negative trend ov er the 2002-2006 years of the study (Figure 4-9). This negative slope at -0.0048 indicates a general mo vement away from funding equity over the 20022006 years of the study. The ANOVA regression resulted in F = 14.168, and a significant regression equation was found (F(1,3) = 14.168, p<.05), significant F = 0.03. McLoone Index Performance Excluded The McLoone index with performance funding excluded decreased for the two years of 2002-03 and 2003-04 from the higher level in 200102 indicating decreasing equity in the distribution for that period (Table 4-16). The statistic reversed upward again in 2004-05 indicating increasing equity for that year, but decreased in the final year of the study. The skewness of the distribution, same as for the C.V., is positive in 2001-02 and negative the remaining years indicating outliers at the lower end of the per-student FTE revenue in the distribution. The slope of the pred icted McLoone index with performance fundingexcluded shows a negative trend ov er the 2002-2006 years of the study (Figure 4-10). This negative slope at -0.0043 indicates a move aw ay from funding equity over the 2002-2006 years of the study, although slightly improved compared to McLoone with performance included. The ANOVA regression resulted in F = 6.62, and a significant regression equation was not found (F(1,3) = 6.62, p<.05), significant F = 0.08.

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92 Gini Coefficient Performance Included The Gini Coefficient is defined as the sum of all variances among operating revenues and student FTEs for each of the districts within a system divided by a denominator of the mean revenue per-student FTE times two of the square of the total FTEs for the system. Thompson, Wood, and Honeyman (1994) described the Gini Co efficient as a measure that indicates how far the distribution is from providing each percentage of a population w ith the same percentage of a variable, such as per-student FTE operating revenu e. The formula yields a value from zero to one where the smaller the value of the Gini coef ficient, the more equita ble the distribution of per-student FTE operating revenue s in providing a percentage of students with the same percentage of operating revenues. The Gini coefficient was calculated for the five-year study period 2002-2006 with performance funding included and with academic program-cost-weighted per-student FTE revenue performance funding included and exclud ed. In addition, the Gini Coefficient was calculated for each year of the study with non-program-cost-weighted revenue per-student FTE with performance funds included an d excluded. The additional ca lculations and analysis were performed to test whether Gini coefficients w ith performance funds excluded would increase as in Yancey (2002, Tables 4-11 and 412). Results are provided below. Gini Coefficient Performance Included: Program-Cost-Weighted FTE The Gini coefficient with academic program cost-costs-weighted performance funding included increased for year 2002-03 from the first year in the study 2001-02; indicating decreasing equity (Table 4-17). The Gini decreased slightly in the following year 2003-04 indicating a move towards increased equity. The Gini increased the final two years 2004-05 and 2005-06 indicating continuing decrease in equity. Overall, the Gini indicated one year of improving equity and three years of decreasing equity to a high value of 0.119730 in the final

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93 year of the study when measuring per-student FTE revenue with program cost-costs-weighted performance funding included (Table 4-17). The skewness of the distribution with pr ogram cost-weighted performance funding included is positive in 2001-02 and then turns negative for years 2002-03 through 2005-06 indicating outliers at the upper end of the pe r-student FTE revenue in the distribution (Table 41). The slope of the predicted Gini with pr ogram cost-costs-weighted performance funding included shows a positive trend over the 2002-2006 years of the study (Figure 4-11). This positive slope at 0.00075 indicates a general mo ve away from funding equity over the 2002-2006 years of the study. The ANOVA regression resulted in F = 28.07, and a significant regression equation was found (F(1,4) = 28.07, p<.05), significant F = 0.013. Gini Coefficient Performance Excl uded: Program-Cost Weighted FTE The Gini coefficient with academic program cost-weighted performance funding excluded increased for year 2002-03 from the first year in the study 2001-02; indicating decreasing equity (Table 4-18). The Gini decreased slightly in the following year 2003-04 indicating a move towards increased equity. Th e Gini increased in 2004-05 but, unlike with performance included decreased the final year 2005-06 with performan ce excluded indicating an increase in equity. Overall, the Gini indica ted two years of improving equity and two years of increasing equity. It is importa nt to note also the values of Gini with program cost-weighted performance funding excluded (Table 4-18) decreased each year of the study when compared to Gini with program-cost-weighted performance funding included (Table 4-17) to a high value of 0.119730 in the final year of the study when m easuring per-student FTE revenue with program cost-costs-weighted performance funding included The skewness of the distribution with pr ogram cost-weighted performance funding excluded is positive in 2001-02 and the tu rns negative for years 2002-03 through 2005-06

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94 indicating outliers at the upper end of the pe r-student FTE revenue in the distribution (Table 43). The slope of the predicted Gini with pr ogram cost-weighted perf ormance funding excluded shows a positive trend over the 2002-2006 years of the study (Figure 4-12). This positive slope at 0.00076 indicates a general movement away from funding equity ove r the 2002-2006 years of the study. The ANOVA regression resulted in F = 24.09, and a significant regression equation was found (F(1,4) = 24.09, p<.05), significant F = 0.016. Gini Coefficient Performance Include d: Non-Program-Cost Weighted FTE The Gini coefficient with non-academic pr ogram-cost-weighted performance funding included decreased for the two years 2002-03 and 2003-04 from the first year in the study 200102; indicating increasing equity (Table 4-19). The increasing equity trend reversed in 2004-05 and 2005-06 when the Gini increased from the 2004-05 low of 0.044780 to a high for the study of 0.49329 in 2005-06. Overall, the Gini with no n-academic program-cost-weighted performance funding included indicated two years of improving e quity and two years of decreasing equity to the high value of 0.49329 in the final year of th e study when measuring per-student FTE revenue with non-program cost-weighted performance funding included (Table 4-19). The skewness of the distribution with nonprogram cost-weighted performance funding included is positive each year of the study indicat ing outliers at the upper end of the per-student FTE revenue in the distribution (Table 4-5 ). The slope of the predic ted Gini with non-program cost-weighted performance funding included show s a positive trend over the 2002-2006 years of the study (Figure 4-13). This positive slope at 0.00054 indica tes a general movement away from funding equity over the 2002-2006 ye ars of the study. The ANOVA regression resulted in F = 1.36, and a significant regression equation was no t found (F(1,4) = 1.36, p<.05), significant F = 0.327.

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95 Gini Coefficient Performance Exclude d: Non-Program-Cost Weighted FTE The Gini coefficient with non-academic program cost-weighted performance funding excluded decreased for two years 2002-03 and 2003-04 from the firs t year in the study 2001-02 ; indicating increasing equity (Table 4-20). The Gini increased noticea bly in the next two years 2004-05 and 2005-06 indicating a reversal towards decr easing equity. Overall, the Gini indicated two years of improving equity and three years of decreasing equity to a high value of 0.049582 in the final year of the study when measuring per-student F TE revenue with program costweighted performance funding included (Table 4-20). The skewness of the distribution with nonprogram cost-weighted performance funding excluded is positive each year of the study indicating outliers at the upper end of the per-student FTE revenue in the distribution (Table 4-6 ). The slope of the predic ted Gini with non-program cost-weighted performance funding excluded show s a positive trend over the 2002-2006 years of the study (Figure 4-14). This positive slope at 0.00058 indica tes a general movement away from funding equity over the 2002-2006 ye ars of the study. The ANOVA regression resulted in F = 1.57, and a significant regression equation was no t found (F(1,4) = 1.57, p<.05), significant F = 0.298. Research Question Two Research question two centered on exploring methods of increasing fiscal equity in funding distributions when performance funds are included. In particular: (2) What effects will indexing the appropriations of applicable performance funds to the proportions of selected speci al population groups Black Males and Hispanics have on horizontal equity in the dist ribution of operating funds for Floridas 28 public community colleges for the years 2001-02 through 2005-06? To answer research question two, raw da ta for State support was obtained from the Florida Department of Education as described above for research question one. Population data

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96 by county and age groups for Black males, and Hi spanics was obtained from the University of Florida Bureau of Economic and Business Rese arch for years 2002-2006. A special population demographics adjustment (SPDA) index was calculated by the researcher for each college. Actual performance funding distributions for FCCS Performance Measure II (special populations) for years 2002-2006 were re-distrib uted based on the SPDA index. Details on SPDA methodology are provided in chapter 3. Th e totals of Measure II performance funding distributions before and after SPDA rema ined equal for each year of the study (Table 4-34 and Table 4-35). The six statistics measures of Range, Restricted Range, Federal Range Ratio, Coefficient of Variation, McLoone Index, and Gini coefficient were used to examine the influence of SPDA-performance funding on horiz ontal equity among the colleges for the five years of the study. Range With Special Population Demographics Adjusted Performance Included The range with SPDA-performance included decreased in year 2002-03 from the first year 2001-02; indicating increasing equity (Table 4-24). The equity increase in 2002-03 was driven largely by a $576 decrease in the highest range value that year. The increasing equity trend reversed in each of the next three ye ars 2003-04, 2004-05 and 2005-06 driven by increases in the lowest range values but more so by larger increases in the highest range values for each year. This indicates colleges with already high per-student FTE revenue received additional gains. Overall, the range with SPDA-perfor mance funding included indicated one year of improving equity and three year s of decreasing equity compar ed to the beginning year 2001-02 (Table 4-24). The skewness of the distribution with SPDAperformance funding included is slightly positive for year 2001-02 (0.21) but moved to slightly negative (-0.21 to -0.009) for the remaining years 2002-03 through 2005-06. This i ndicates more outlier pe r-student FTE revenue

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97 values at the lower end of the distribution (Table 4-21 ). The slope of the predicted range with SPDA-performance funding included shows a pos itive trend over the 2002-2006 years of the study (Figure 4-15). This positive slope at 103.14 indicates a general movement away from funding equity over the 2002-2006 ye ars of the study. The ANOVA regression resulted in F = 0.84, and a significant regression equation was no t found (F(1,4) = 0.84, p<.05), significant F = 0.427. It is noteworthy that the range with SP DA-performance included was equal to the same value 3,497 for year 2001-02, and was lower fo r year 2002-03. However, range with SPDAperformance exceeded the range with non-SPDA performance included for the three years 200304, 2004-05, and 2005-06 (Table 4-7) Restricted Range With Special Populat ion Demographics Adjusted Performance Included The restricted range with SPDA-performance included increased in year 2002-03 from year 2001-02; indicating decreasing equity (Table 4-25). This equity decrease was driven largely by a $247 increase in the highest re stricted range value that year. The decreasing equity trend continued for each the next three years 2003-04, 2004-05 and 2005-06 driven by some increases in the lowest restricted range values but more so by larger increases in the highest restricted range value for each year. This indicates colle ges with already high per-student FTE revenue received additional gains. Over all, the restricted range with SPDA-performance funding included indicated no years of improving equity. The skewness of the restricted range di stribution with SPDA-performance funding included was negative for each year of the st udy (-0.088 to -0.218) indicating more outlier perstudent FTE revenue values at th e lower end of the distribution (Table 4-22). The slope of the predicted restricted range w ith SPDA-performance-funding included shows a positive trend over the 2002-2006 years of the study (Figure 4-16). This positive slope at 211.29 indicates a general

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98 movement away from funding equity over the 20 02-2006 years of the study when measuring the restricted range with SPDA-performance-funding included. The ANOVA regression resulted in F = 13.77, and a significant regression equati on was found (F(1,4) = 13.77, p<.05), significant F = 0.034 It is important to note that the values of the restricted range with SPDA-performance funding included are lower than the values of restricted ra nge with non-SPDA performance included (Table 4-9) for four years 2001-02 and 2003-04 through 2005-06 and decreased by small decimal points (not reflected due to r ounding) for year 2002-03; 2,257.67 compared to 2,257.71 with non-SPDA-Performance included. Federal Range Ratio With Special Population Demographics Adjusted Performance Included The federal range ratio with SPDA-performa nce included increased in years 2002-03 and 2003-04 from 2001-02; indica ting decreasing equity (Table 4-26). The federal range ratio statistic decreased slightly in 2004-05 from 0.86720 to 0.86177 (-.00543, or .62%) indicating a small move towards improved equity. Overall, the federal range ratio with SPDA-performance funding included indicated one year of improving equity. The skewness of the federal range distribu tion with SPDA-performance funding included is the same as for the restricted range with SPDA-performance included: negative for each year of the study (-0.088 to -0.218) indicating more outlier per-student FTE revenue values at the lower end of the distribution (Table 4-22 ). The slope of the federal range ratio with SPDAperformance-funding included shows a positiv e trend over the 2002-2006 years of the study (Figure 4-17). This positive slope at 0.044 indicates a general movement away from funding equity over the 2002-2006 years of the study when measuring with the federal range ratio with SPDA-performance-funding included. The ANOVA regression resulted in F = 12.16, and a significant regression equation was found (F(1,4) = 12.16, p<.05), significant F = 0.039. It is

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99 important to note that the values of the fe deral range ratio with SPDA-performance funding included are lower than the values of federa l range ratio with non-SPDA performance included (Table 4-11) for four years 2001-02 and 2003-04 through 2005-06. Coefficient of Variation With Special Po pulation Demographics Adjusted Performance Included The coefficient of variation (C.V.) with SPDA-performance funding included decreased for the year 2002-03 from the previous years higher level in 200102 indicating increasing equity in the distribution for that period (Table 4-27). The C.V. statistic increased in 2003-04 indicating decreasing equity, revers ed in 2004-05 back to increased equity. The statistic reversed upward again in 2005-06 indicating d ecreasing equity in the distribu tion in the last year of the study. Overall, horizontal fiscal equity as meas ured by the C.V. statisti c with SPDA-performance funding included decreased two years and increased two (Table 4-27). The skewness of the distribution is positive in 2001-02 and negative the remaining years indicating outliers at the lower end of the per-student FTE revenue in the distribution (Table 421) The slope of the predicted C.V. with SP DA-performance funding included shows a positive trend over the 2002-2006 years of the study (Figure 4-18). This positive slope at 0.0012 is small, indicating generally a slight movement away from funding equity ove r the 2002-2006 years of the study, is small. The ANOVA regression at F-significance (F(1,3) = 0.536, p< .05) with F significance at .51 indicate that a significan t regression equation w ith performance funds included was not found. It is important to note that the values of the C.V. with SPDAperformance funding included are lower than the values of C.V. with non-SPDA performance included (Table 4-14) for three years 2001-02, 2002-03, and 2003-04.

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100 McLoone Index With Special Population Dem ographics Adjusted Performance Included The McLoone index with SPDA-performan ce funding included decreased in 2002-03 from the high value in the prior year 2001-02 indi cating declining equity for the colleges in the lower half of the per-student F TE revenue distribution that year (Table 4-28). The index increased and reversed towards improved equity in 2003-04. It reversed and decreased for the final two years of the study 2004-05 a nd 2005-06 indicating decreasing equity for the colleges in the lower half of the per-st udent FTE revenue distribution. The skewness of the distribution, same as for the C.V., is positive in 2001-02 and negative the remaining years indicating outliers at the lower end of the per-student FTE revenue in the distribution. The slope of the predic ted McLoone index with SPDA-performance fundingincluded shows a negative trend ov er the 2002-2006 years of the study (Figure 4-19). This negative slope at -0.0017 indicates a general mo vement away from funding equity over the 20022006 years of the study. The ANOVA regression at F-significance (F(1/3)= 0.2.37, p< .05) with F significance at .22 indicate that a significant regression eq uation with performance funds included was not found. It is important to note that the values of the McLoone in Table 4-28 are lower than the corresponding values in Table 4-15 for three years 2001-02, 2002-03, and 200304 indicating less equity. Ho wever, the McLoone in Table 4-28 are higher than the corresponding values in Table 4-15 in the final two years 200405 and 2005-06 indicating greater equity when measuring with McLoone and with SPDA-performance included. Gini Coefficient With Special Population Demographics Adjusted Performance Included: Program-Cost Weighted FTE The Gini coefficient with academic-progr am cost-weighted SPDA-performance funding included increased each of th e five years of the study (Table 4-29). The 2001-02 Gini value at 0.116081 was the lowest for the five years, th e 2005-06 value of 0.119898 the highest. This

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101 indicates an overall decline of e quity in the distribution of per-st udent operating re venues to the same percentages of student FTEs. The skewness of the Gini distribution with program cost-weighted SPDA-performance funding included is positive for each year of the study 2001-2 at 1.57 through 2005-06 at 12.06 indicating outliers at the upper end of the pe r-student FTE revenue in the distribution (Table 421) The slope of the predicted Gini with pr ogram cost-weighted SPDA-performance funding included shows a positive trend over the 2002-2006 years of the study (Figure 4-20). This positive slope at 0.00117 indicates a general move ment away from funding equity over the 20022006 years of the study. The ANOVA regression resulted in F = 35.06, and a significant regression equation was found (F(1,3) = 35.06, p<.05), significant F = 0.009. For this research question two, it is important to note that the values of the Gini in Table 4-29 are lower than the co rresponding values in Table 4-17 for three years 2002-03, 2003-04 and 2004-05 indicating more equity in the distribution when measuring with Gini with program-costweighted FTE and with SPDA-performance incl uded. For year 2005-06, the Gini coefficient value with SPDA-performance funds included was higher than the corresponding value in Table 4-17 indicating a less favorable equity distribut ion in 2005-06 with SPD A-performance funds included. Gini Coefficient With Special Population Demographi cs Adjusted Performance Included (Non-Program-Cost Weighted) The Gini coefficient with non-academic program-cost-weighted SPDA-performance funding included decreased for the two years 2002-03 and 2003-04 from the first year in the study 2001-02; indicating increasing equity (Table 4-30). The increasing equity trend reversed in 2004-05 and 2005-06 when the Gini increased from a low of 0.044881 to a high for the study of 0.050272 in 2005-06. Overall, the Gini with non-academic program-cost-weighted SPDA-

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102 performance funding included indicated two y ears of improving equity and two years of decreasing equity when measuring per-student FTE revenue with non-program cost-weighted SPDA-performance funding included The skewness of the distribution with nonprogram cost-weighted SPDA-performance funding included is positive for each year of the study 2001-2 at 1.57 through 2005-06 at 12.06 indicating outliers at the upper end of the pe r-student FTE revenue in the distribution (Table 423). The slope of the predicted Gini with non-program cost-weighted SPDA-performance funding included shows a positive tre nd over the 2002-2006 years of the study (Figure 4-21). This positive slope at 0.0012 indi cates a general movement away from funding equity over the 2002-2006 years of the study. The ANOVA regression resulted in F = 1.83, and a significant regression equation was not found (F(1,3) = 1.83, p<.05), significant F = 0.268. For this research question two, it is important to note that the values of the Gini in Table 4-30 are lower than the co rresponding values in Table 4-17 for three years 2001-02, 2002-03 and 2003-04 indicating more equity in the distribution when measuring with Gini with program-costweighted FTE and with SPDA-performance included than with non-SPDA-performance included. For year 2005-06, the Gini coeffici ent value with non-program-cost-weighted SPDAperformance funds included was higher than the corresponding value in Table 4-17 indicating a less favorable equity distribution in 2005-06 with SPDA-performance funds included. This is also significant as the values in Table 4-30 are also generally sm aller than the Gini values in Yancey (2002) Tables 4-11 and 4-12. Bivariate Correlation Analysis: Before and After SPDA Performance Bivariate correlation analysis was used to di scern the strengths of relationships between populations of Black males a nd Hispanics in each college service area and Measure II performance funding before and after SPDA adjust ment. Counties in each colleges service area

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103 were obtained from the Florida Comm unity Colleges System FACT Book (Table 3-1). One-way ANOVA with mean plots and frequency analysis with histograms were used to determine the normality of the population distributions by coll ege service areas. The populations of Black males and Hispanics were not normally distributed (Figures 4-22, 4-23, 4-24, and 4-25). Consequently Spearmans rho bivariate correlation analysis was used to estimate strength of relationship between populations of Black males and Hispanic s in each service area and corresponding Measure II performance f unding before and after SPDA adjustment. The Spearmans rho correlation coefficien ts indicated strong positive relationships between populations of Black males and Hisp anics in each service area and corresponding Measure II performance funding for both before and after SPDA adjustment (Table 4-31). The positive relationship found at (rho (28) = .808, p< .01) thorough (rho (28) = .837, p< .01) for populations of Black males and Hispanics before SPDA adjustment is slightly higher than the (rho (28) = .718, p< .01) thor ough (rho (28) = .784, p< .01) fo r populations of Black males and Hispanics after SPDA adjustment. This slight difference may be expl ained by other special populations funding in Measure II, such as di sabled students, that may or may not be proportional distributed in the populati ons of Black males and Hispanics. Lorenz Curve Berne and Stiefel (1984) describe the Lorenz curve as an appropriate way to show the meaning of he Gini coefficient graphically: Given any distribution of per-student FTE revenue funding, if the per-student FTE funding in arranged by school in ascending order along with each schools FTEs, a relationship between cumulative per-student revenues and cumulative per-student FTEs can be shown graphically. The relationship can be plotted on a graph that has the cumulative percent of students on the x-axis and the cumulative percent of per-student revenues on the y-axis. Berne and Stiefel expl ain that for a perfectly equal distribution (all students receive the same per-student revenue funding) the graph would be a 45degree line running diagonally from the lower-le ft corner of the graph (0%, 0%) to the upper-right corner of the graph (100%, 100%). Any distribution that is not perfectly equal

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104 would be graphed as a curve below the 45-degree line. The more unequal the distribution, the further below the 45-degree li ne the curve would lie. The curve below the 45-degree line is the Lorenz curve. The Gini coefficient is defined as the area between the Lorenze curve and the 45-deg ree line (Berne, Stiefel, 1984, p66-67). Lorenz Curves With and Without Perf ormance Funds Program Cost-Weighted Lorenz curves with program-cost-weight ed with performance fund included and performance funds excluded indicate a noticeable amount of space betwee n the 45-degree perfect equity lines and the Lorenz curves (Figures 4-26, 4-27, 4-28, 4-29, 4-30). The space indicates inequity in the cumulative distributions of st udent FTEs and per-student FTE revenues when measuring with program-cost-weighted performance included. Lorenz Curves With and Without Perfor mance Funds Non-Program Cost-Weighted Lorenz curves with and wit hout non-program-cost-weighted performance funds indicate some space between the 45-degree perfect equity lines and the Lorenz curves (Figures 4-31, 432, 4-33, 4-34, and 4-35). This visibly smalle r space indicates less inequity in the cumulative distributions of student FTEs and per-student FTE revenues when measuring with non-programcost-weighted performance funds than with program-cost-weighted performance (Figures 4-26, 4-27, 4-28, 4-29, and 4-30). These Lorenz curves and the visibly smaller spaces are more similar to Yancey (2002) Figures 4-13through 4-18. Lorenz Curves With SPDA Adjusted a nd NonSPDA-Adjusted-Performance Funds Non-Program Cost-Weighted Lorenz curves with SPDA-adjusted and non-SPDA-adjusted performance funds (i.e., before SPDA-adjustments were made) and which are non-program-cost-we ighted indicate some space between the 45-degree perfect equity line and the Lorenz curv es (Figures 4-36, 4-37, 4-3, 4-39, and 4-40). The space between the perfect equ ity line and the Lorenz curves is similar in size to those in Figures 4-16 th rough 4-30. The differences in the space sizes for SPDA-adjusted and non-SPDA-adjusted performance f unds are largely indiscernible.

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105 Summary In this chapter, the data analysis process was presented. Six measures of horizontal fiscal equity were used to assess changes in fiscal equity for per-student F TE revenue distributions with performance funding include d, with performance funding excluded, and with special population demographically-adjusted performance funding included. In chapter five, discussion of the results, implications for higher educati on administrators, and suggestions for further research will conclude this study.

PAGE 106

106 Table 4-1. Descriptive statisti cs for range, coefficient of vari ation, McLoone index and Gini coefficient for operating funds per FTE for Florida community colleges with performance funds included. 2001-022002-032003-042004-052005-06 Mean3884.213193933.786003965.083114246.684734514.22210 Standard Error165.99899159.78872168.10817176.13896192.17342 Median3888.471743986.147924004.508564298.622734602.59873 Standard Deviation878.38411845.52241889.54484932.039791016.88618 Sample Variance771558.65078714908.14754791290.01550868698.174471034057.50615 Kurtosis-0.61340-1.26467-1.39314-1.14652-1.02074 Skewness0.21253-0.10800-0.09149-0.19174-0.11856 Range3496.709142830.089052748.924133188.218783472.12832 Minimum2417.471312508.910192454.374202572.962252760.61525 Maximum5914.180455338.999245203.298325761.181036232.74356 Sum108757.96929110146.00810111022.32714118907.17234126398.21875 C o u n t2 82 82 82 82 8 o nfidence Level (95.0%)340.60180327.85936344.92947361.40730394.30729 Table 4-2. Descriptive statisti cs for restricted range and fede ral range ratio for operating funds per FTE for Florida community colleges with performance funds included. 2001-022002-20032003-20042004-20052005-2006 Mean3914.792593944.930944029.252584313.451044580.98435 Standard Error145.90974147.74032161.62163163.13833178.46479 Median4004.002903986.147924164.387594564.064234878.92145 Standard Deviation729.54872723.77677808.10813815.69163892.32396 Sample Variance532241.33762523852.81785653038.75038665352.82812796242.04815 Kurtosis-1.40032-1.43236-1.43523-1.22720-0.97019 Skewness-0.05020-0.09037-0.06239-0.20368-0.14539 Restricted Range2307.940312257.705592373.870742665.064083204.42330 Minimum2837.705892798.206992816.089312974.533942924.98378 Maximum5145.646195055.912585189.960055639.598036129.40708 Sum97869.8148394678.34252100731.31438107836.27590114524.60864 Count2524252525 Confidence Level (95.0%)301.14291305.62413333.57064336.70095368.33322

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107 Table 4-3. Descriptive statisti cs for range, coefficient of vari ation, McLoone index and Gini coefficient for operating funds per FTE for Florida community colleges with performance funds excluded. 2001-022002-032003-042004-052005-06 Mean3859.144553910.441053942.481114224.011184459.32840 Standard Error165.15990158.96588167.35022175.41566190.39046 Median3861.745283962.332823975.894634276.908364531.23852 Standard Deviation873.94404841.16838885.53415928.212411007.45164 Sample Variance763778.18483707564.24733784170.73138861578.271211014958.80210 Kurtosis-0.59185-1.25768-1.38513-1.13895-1.00996 Skewness0.22145-0.10290-0.08429-0.18616-0.10828 Range3490.427272828.157092742.036233170.049103432.71526 Minimum2401.395672494.144112440.363042558.515642726.49441 Maximum5891.822945322.301205182.399275728.564736159.20968 Sum108056.04740109492.34934110389.47097118272.31294124861.19513 C o u n t2 82 82 82 82 8 o nfidence Level (95.0%)338.88012326.17104343.37429359.92319390.64896 Table 4-4. Descriptive statisti cs for restricted range and fede ral range ratio for operating funds per FTE for Florida community colleges with performance funds excluded. 2001-022002-20032003-20042004-20052005-2006 Mean3888.864083965.986383952.565724471.086614722.00411 Standard Error144.94947147.82792163.50116146.24653158.64821 Median3981.260854030.696073975.894634626.307874851.21866 Standard Deviation724.74734739.13961833.69562685.95703744.12606 Sample Variance525258.71159546327.36653695048.39332470537.04851553723.59790 Kurtosis-1.40908-1.42095-1.41040-1.36176-1.11340 Skewness-0.05119-0.11731-0.03814-0.132840.03633 Restricted Range2281.962372259.521452538.255912208.424102486.94416 Minimum2823.311752784.172542618.195673418.534163599.41949 Maximum5105.274125043.693995156.451595626.958266086.36366 Sum97221.6020699149.65939102766.7086698363.90537103884.09035 Count2525262222 Confidence Level (95.0%)299.16100305.10183336.73695304.13631329.92701

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108 Table 4-5. Descriptive statisti cs for range, coefficient of vari ation, McLoone index and Gini coefficient for non-program-cost-weighted operating funds per FTE for Florida community colleges with performance funds included. 2001-022002-032003-042004-052005-06 Mean4775.303684800.667874792.119875117.294105446.58680 Standard Error174.04715158.60930177.80398176.28830195.60606 Median4484.741884616.216374506.360774864.748265193.29678 Standard Deviation920.97094839.28153940.85021932.830011035.05000 Sample Variance848187.47034704393.49158885199.11322870171.834081071328.49457 Kurtosis1.408481.953433.854595.615995.75712 Skewness1.574081.641712.032462.187232.13298 Range3142.439803181.894083815.352524233.210605053.21712 Minimum3856.099013902.144983916.994534226.186444140.89350 Maximum6998.538817084.039067732.347058459.397049194.11062 Sum133708.50307134418.70038134179.35629143284.23468152504.43048 Count 28 28 28 28 28 Confidence Level (95.0%)357.11525325.43940364.82362361.71371401.35049 Table 4-6. Descriptive statisti cs for range, coefficient of vari ation, McLoone index and Gini coefficient for non-program-cost-weighted operating funds per FTE for Florida community colleges with performance funds excluded. 2001-022002-032003-042004-052005-06 Mean4744.912834772.619904765.391575090.448685381.23967 Standard Error173.83967158.50880177.86549176.40881195.37506 Median4453.234534585.455504470.745954843.541085131.10863 Standard Deviation919.87306838.74974941.17569933.467661033.82763 Sample Variance846166.44893703501.11983885811.68033871361.865541068799.57788 Kurtosis1.430101.974103.873415.651815.79963 Skewness1.582871.649492.036632.192832.14037 Range3135.723903177.265993812.287164252.436445045.47735 Minimum3839.599433887.608863900.889534188.000954084.06813 Maximum6975.323337064.874857713.176698440.437399129.54548 Sum132857.55933133633.35712133430.96396142532.56296150674.71065 Count 28 28 28 28 28 Confidence Level (95.0%)356.68953325.23319364.94983361.96097400.87650

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109 Table 4-7. Range for operating funds per FTE fo r Florida community colle ges with performance funds included. Year Range Low High Skewness 2001-02 3,497 2,417 5,914 0.21253 2002-03 2,830 2,509 5,339 -0.10799 2003-04 2,749 2,454 5,203 -0.09148 2004-05 3,188 2,573 5,761 -0.19174 2005-06 3,472 2,761 6,233 -0.11856 0.0000 500.0000 1,000.0000 1,500.0000 2,000.0000 2,500.0000 3,000.0000 3,500.0000 4,000.0000 20022003200420052006 Fiscal YearsDollar s Range with Performance Predicted Range with Performance Figure 4-1. Range and predicted range for ope rating funds per FTE with performance funds included.

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110 Table 4-8. Range for operating funds per FTE fo r Florida community colle ges with performance funds excluded. Year Range Low High Skewness 2001-02 3,490 2,401 5,892 0.22145 2002-03 2,828 2,494 5,322 -0.10290 2003-04 2,742 2,440 5,182 -0.08429 2004-05 3,170 2,559 5,729 -0.18616 2005-06 3,433 2,726 6,159 -0.10827 500.0000 1,000.0000 1,500.0000 2,000.0000 2,500.0000 3,000.0000 3,500.0000 4,000.0000 20022003200420052006 Fiscal YearsDollar s Range without Performance Predicted Range without Performance Figure 4-2. Range and predicted range for ope rating funds per FTE with performance fund excluded.

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111 Table 4-9. Restricted range for operating funds per FTE for Fl orida community colleges with performance funds included. Year Range Low High Skewness 2001-02 2,308 2,838 5,146 -0.05020 2002-03 2,258 2,798 5,056 -0.09037 2003-04 2,374 2,816 5,190 -0.06239 2004-05 2,665 2,975 5,640 -0.20368 2005-06 3,204 2,925 6,129 -0.14539 500.0000 1,000.0000 1,500.0000 2,000.0000 2,500.0000 3,000.0000 3,500.0000 20022003200420052006 Fiscal YearsDollar s Restricted Range with Performance Predicted Restricted Range with Performance Figure 4-3. Restricted range fo r operating funds per FTE for Florida community colleges with performance funds included.

PAGE 112

112 Table 4-10. Restricted range fo r operating funds per FTE for Florida community colleges with performance funds excluded. Year Restricted Range Low High Skewness 2001-02 2,282 2,823 5,105 -0.05118 2002-03 2,260 2,784 5,044 -0.11731 2003-04 2,538 2,618 5,156 -0.03814 2004-05 2,208 3,419 5,627 -0.13284 2005-06 2,487 3,599 6,086 -0.03633 2,000.0000 2,100.0000 2,200.0000 2,300.0000 2,400.0000 2,500.0000 2,600.0000 20022003200420052006 Fiscal YearsDollars Restricted Range without Performance Predicted Restricted Restricted without Performance Figure 4-4. Restricted range fo r operating funds per FTE for Florida community colleges with performance funds excluded.

PAGE 113

113 Table 4-11. Federal range ratio for operati ng funds per FTE for Florida community colleges with performance funds included. Year Federal Range Ratio Skewness 2001-02 0.86931 -0.05020 2002-03 0.85791 -0.09037 2003-04 0.88009 -0.06239 2004-05 0.94507 -0.20368 2005-06 1.10654 -0.14539 0.00000 0.20000 0.40000 0.60000 0.80000 1.00000 1.20000 20022003200420052006 Fiscal YearsRatio Fed Ratio with Performance Predicted Fed Ratio with Performance Figure 4-5. Federal range ratio for operating funds per FTE for Florida community colleges with performance funds included.

PAGE 114

114 Table 4-12. Federal range ratio for operati ng funds per FTE for Florida community colleges with performance funds excluded. Year Federal Range Ratio Skewness 2001-02 0.86439 -0.05118 2002-03 0.86356 -0.11731 2003-04 0.94598 -0.03814 2004-05 0.78747 -0.13284 2005-06 0.86991 -0.03633 0.00000 0.10000 0.20000 0.30000 0.40000 0.50000 0.60000 0.70000 0.80000 0.90000 1.00000 20022003200420052006 Fiscal YearsRatio Federal Ratio without Performance Predicted Fed Ratio without Performance Figure 4-6. Federal range ratio for operating funds per FTE for Florida community colleges with performance funds excluded.

PAGE 115

115 Table 4-13. Coefficient of va riation for operating funds per F TE for Florida community colleges with performance funds included. Year Coefficient of Variation Skewness 2001-02 0.226142 0.21253 2002-03 0.214939 -0.10799 2003-04 0.224345 -0.09148 2004-05 0.219475 -0.19174 2005-06 0.225263 -0.11856 0.208000 0.210000 0.212000 0.214000 0.216000 0.218000 0.220000 0.222000 0.224000 0.226000 0.228000 20022003200420052006 Fiscal YearsCoefficient Coefficient of Variation With Performance Predicted Coefficient of Variation with Performance Figure 4-7. Coefficient of vari ation for operating funds per F TE for Florida community colleges with performance funds included.

PAGE 116

116 Table 4-14. Coefficient of va riation for operating funds per F TE for Florida community colleges with performance funds excluded. Year Coefficient of Variation Skewness 2001-02 0.226461 0.22145 2002-03 0.215108 -0.10290 2003-04 0.224613 -0.08429 2004-05 0.219747 -0.18616 2005-06 0.225920 -0.10827 0.208000 0.210000 0.212000 0.214000 0.216000 0.218000 0.220000 0.222000 0.224000 0.226000 0.228000 20022003200420052006 Fiscal YearsCoefficient Coefficient without Performance Predicted Coefficient without Performance Figure 4-8. Coefficient of vari ation for operating funds per F TE for Florida community colleges with performance funds excluded.

PAGE 117

117 Table 4-15. McLoone index for operating funds per FTE for Florida community colleges with performance funds included. Year McLoone Index Skewness 2001-02 0.784043 0.21253 2002-03 0.769089 -0.10799 2003-04 0.761605 -0.09148 2004-05 0.761397 -0.19174 2005-06 0.757718 -0.11856 0.74000 0.74500 0.75000 0.75500 0.76000 0.76500 0.77000 0.77500 0.78000 0.78500 0.79000 20022003200420052006 Fiscal YearsIndex McLoone with Performance Predicted McLoone with Performance Figure 4-9. McLoone index for operating funds per FTE for Florida community colleges with performance funds included.

PAGE 118

118 Table 4-16. McLoone index for operating funds per FTE for Florida community colleges with performance funds excluded. Year McLoone Index Skewness 2001-02 0.994265 0.22145 2002-03 0.981141 -0.10290 2003-04 0.981135 -0.08429 2004-05 0.984422 -0.18616 2005-06 0.965574 -0.10827 0.950000 0.955000 0.960000 0.965000 0.970000 0.975000 0.980000 0.985000 0.990000 0.995000 1.000000 20022003200420052006 Fiscal YearsIndex McLoone Index without Performance Predicted McLoone Index without Performance Figure 4-10. McLoone index for operating funds pe r FTE for Florida community colleges with performance funds excluded.

PAGE 119

119 Table 4-17. Gini Coefficien t for Operating Funds per FTE for Florida Community Colleges With Performance Funds Included. Year Gini Coefficient Skewness 2001-02 0.116044 0.21253 2002-03 0.117624 -0.10799 2003-04 0.117577 -0.09148 2004-05 0.119642 -0.19174 2005-06 0.119730 -0.11856 0.114000 0.115000 0.116000 0.117000 0.118000 0.119000 0.120000 0.121000 20022003200420052006 Fiscal YearsGini Gini Coefficient with Performance Predicted Gini Coefficient with Performance Figure 4-11. Gini coefficient for operating funds per FTE for Florida community colleges with performance funds included.

PAGE 120

120 Table 4-18. Gini coefficient for operating funds for Florida community colleges with performance funds excluded. Year Gini Coefficient Skewness 2001-02 0.115792 0.22145 2002-03 0.117459 -0.10290 2003-04 0.117360 -0.08429 2004-05 0.119530 -0.18616 2005-06 0.119519 -0.10827 0.113000 0.114000 0.115000 0.116000 0.117000 0.118000 0.119000 0.120000 0.121000 20022003200420052006 Fiscal YearsGini Gini Coefficient without Performance Predicted Gini Coefficient without Performance Figure 4-12. Gini coefficient for operating funds per FTE for Florida community colleges with performance funds excluded.

PAGE 121

121 Table 4-19. Gini coefficient for operating funds per non-program-cost-weighted FTE for Florida community colleges with non-SPDA-adju sted performance funds included. Year Gini Coefficient Skewness 2001-02 0.047332 1.57408 2002-03 0.045086 1.64171 2003-04 0.044780 2.03246 2004-05 0.047922 2.18723 2005-06 0.049329 2.13298 0.042000 0.043000 0.044000 0.045000 0.046000 0.047000 0.048000 0.049000 0.050000 20022003200420052006 Fiscal YearsGini Gini Coefficient with Non-Program-Cost Weighted Performance Predicted Gini Coefficient with Non-Program-Cost Weighted Performance Figure 4-13. Gini coefficient for non-program-costweighted operating funds per FTE for Florida community colleges with non-SPDA-adju sted performance funds included.

PAGE 122

122 Table 4-20. Gini coefficient for operating funds per non-program-cost-weighted FTE for Florida community colleges with performance funds excluded. Year Gini Coefficient Skewness 2001-02 0.047357 1.58287 2002-03 0.045182 1.64949 2003-04 0.044916 2.03663 2004-05 0.048039 2.19283 2005-06 0.049582 2.14037 0.042000 0.043000 0.044000 0.045000 0.046000 0.047000 0.048000 0.049000 0.050000 20022003200420052006 Fiscal YearsGini Gini Coefficient with Non-Program-Cost Weighted Performance Excluded Predicted Gini Coefficient with Non-Program-Cost Weighted Performance Excluded Figure 4-14. Gini coefficient for non-program-costweighted operating funds per FTE for Florida community colleges with performance funds excluded.

PAGE 123

123 Table 4-21. Descriptive statistics for range, coef ficient of variation, McLoone index and Gini coefficient for operating funds per FTE for Florida community colleges with program-cost-weighted special population demographics adjustment performance funds included. 2001-022002-032003-042004-052005-06 Mean3884.496343938.329253970.691224254.436984527.43127 Standard Error165.91924159.03278168.70297178.29173196.16334 Median3906.344834037.047214003.815014295.728804577.86537 Standard Deviation877.96212841.52237892.69222943.431141037.99881 Sample Variance770817.47772708159.89689796899.39533890062.324211077441.52984 Kurtosis-0.61333-1.26415-1.35934-1.03229-0.80526 Skewness0.20686-0.12011-0.06668-0.12676-0.00901 Range3496.731032827.160972871.408833413.750263848.05923 Minimum2415.580702508.843742454.018352571.734332758.46833 Maximum5912.311735336.004715325.427195985.484596606.52756 Sum108765.89748110273.21895111179.35423119124.23546126768.07547 Count 28 28 28 28 28 Confidence Level (95.0%)340.43816326.30831346.14990365.82440402.49392 Table 4-22. Descriptive statistics for restricted range and federa l range ratio for operating funds per FTE for Florida community colleges with program-cost-weighted special population demographics adjustment performance funds included. 2001-022002-032003-042004-052005-06Mean3864.064543951.343443981.906034258.051024516.64751Standard Error142.29754146.92554159.65452159.14216172.14587Median3906.344834037.047214003.815014295.728804577.86537Standard Deviation697.11273719.78521782.14422779.63418843.33910Sample Variance485966.15324518090.75572611749.57713607829.46147711220.83602Kurtosis-1.51194-1.45312-1.42061-1.29895-1.01680Skewness-0.08808-0.09314-0.01279-0.23905-0.21895Ristricted Range1969.388892257.675342338.397042428.804332939.06988Minimum2837.354332796.702472815.821672972.708572925.89753Maximum4806.743235054.377815154.218715401.512905864.96741Sum92737.5489294832.2425895565.74482102193.22459108399.54023C o u n t2 42 42 42 424Confidence Level (95.0%)294.36489303.93864330.27054329.21064356.11087

PAGE 124

124 Table 4-23. Descriptive statistics for Gini coefficient for ope rating funds per FTE for Florida community colleges with non-program -cost-weighted special population demographics adjustment performance funds included. 2001-022002-032003-042004-052005-06 Mean4775.409474806.459104821.529295124.526395459.34577 Standard Error173.74343157.57271182.21077175.97552195.81584 Median4481.139294612.160554535.692214912.445045198.19041 Standard Deviation919.36379833.79639946.79492931.174921036.16002 Sample Variance845229.77699695216.41346896420.62347867086.735371073627.58281 Kurtosis1.417401.999693.672775.581765.55234 Skewness1.577641.651731.988802.165992.06508 Range3141.858873185.224833821.902204234.021485046.95479 Minimum3854.845123896.483283909.425864223.688614142.18709 Maximum6996.703997081.708117731.328068457.710109189.14188 Sum133711.46521134580.85491130181.29074143486.73887152861.68156 Count 28 28 27 28 28 Confidence Level (95.0%)356.49206323.31248374.53959361.07194401.78091

PAGE 125

125 Table 4-24. Range for operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06. Range With SPDA Adjusted Year Performance Funds Low High Skewness 2001-02 3,497 2,416 5,912 0.20686 2002-03 2,827 2,509 5,336 -0.12011 2003-04 2,871 2,454 5,325 -0.06668 2004-05 3,414 2,572 5,985 -0.12676 2005-06 3,848 2,758 6,607 -0.00901 0.0000 1,000.0000 2,000.0000 3,000.0000 4,000.0000 5,000.0000 20022003200420052006 Fiscal YearsDollar s Range with SPDA-Adjusted Performance Predicted Range with SPDA-Adjusted Performance Figure 4-15. Range for operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included.

PAGE 126

126 Table 4-25. Restricted range fo r operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06. Restricted Range With SPDA Adjusted Year Performance Funds Low High Skewness 2001-02 1,969 2,837 4,807 -0.08808 2002-03 2,258 2,797 5,054 -0.09314 2003-04 2,338 2,816 5,154 -0.01276 2004-05 2,429 2,973 5,402 -0.23895 2005-06 2,939 2,926 5,865 -0.21895 500.0000 1,000.0000 1,500.0000 2,000.0000 2,500.0000 3,000.0000 3,500.0000 20022003200420052006 Fiscal YearsDollar s Restricted Range with SPDA-Adjusted Performance Predicted Restricted Range with SPDA-Adjusted Performance Figure 4-16. Restricted range fo r operating funds per FTE for Florida community colleges with special population demographics adjustment index Performance funds included for years 2001-02 through 2005-06.

PAGE 127

127 Table 4-26. Federal range ratio for operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06. Federal Range Ratio With SPDA Adjusted Year Performance Funds Skewness 2001-02 0.74201 -0.08808 2002-03 0.85842 -0.09314 2003-04 0.86720 -0.01276 2004-05 0.86177 -0.23895 2005-06 1.01543 -0.21895 0.00000 0.20000 0.40000 0.60000 0.80000 1.00000 1.20000 20022003200420052006 Fiscal YearsRatio Fed Ratio with SPDA Adjusted Performance Predicted Fed Ratio with None SPDA Adjusted Performance Figure 4-17. Federal range ratio for operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06.

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128 Table 4-27. Coefficient of vari ation for operating funds per F TE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06. Coefficient of Variation With SPDA Adjusted Year Performance Funds Skewness 2001-02 0.226017 0.20686 2002-03 0.213675 -0.12011 2003-04 0.224820 -0.06668 2004-05 0.221752 -0.12676 2005-06 0.229269 -0.00901 0.205000 0.210000 0.215000 0.220000 0.225000 0.230000 0.235000 20022003200420052006 Fiscal YearsCoefficien t Coefficient With SPDA-Adjusted Performance Predicted Coefficient with SPDA-Adjusted Performance Figure 4-18. Coefficient of vari ation for operating funds per F TE for Florida community colleges with special population demographi cs adjustment index performance funds included for years 2001-02 through 2005-06.

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129 Table 4-28. McLoone index for operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06. McLoone Index With SPDA Adjusted Year Performance Funds Skewness 2001-02 0.780468 0.20686 2002-03 0.759136 -0.12011 2003-04 0.761567 -0.06668 2004-05 0.761444 -0.12676 2005-06 0.760601 -0.00901 0.745000 0.750000 0.755000 0.760000 0.765000 0.770000 0.775000 0.780000 0.785000 20022003200420052006 Fiscal YearsInde x McLoone with SPDA-Adjusted Performance Predicted McLoone with SPDA-Adjusted Performance Figure 4-19. McLoone index for operating funds pe r FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06.

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130 Table 4-29. Gini coefficient for operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06. Gini Coefficient With SPDA Adjusted Year Performance Funds Skewness 2001-02 0.116081 0.20686 2002-03 0.117234 -0.12011 2003-04 0.117369 -0.06668 2004-05 0.119634 -0.12676 2005-06 0.119898 -0.00901 0.114000 0.115000 0.116000 0.117000 0.118000 0.119000 0.120000 0.121000 20022003200420052006 Fiscal YearsGini Gini Coefficient with SPDA-Adjusted Performance Predicted Gini Coefficient with SPDA-Adjusted Performance Figure 4-20. Gini coefficient for operating funds per FTE for Florida community colleges with special population demographics adjustment index performance funds included for years 2001-02 through 2005-06.

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131 Table 4-30. Gini coefficient for operating funds per non-program-cost-weighted FTE for Florida community colleges with special populat ion demographics index performance funds included for years 2001-02 through 2005-06. Year Gini Coefficient Skewness 2001-02 0.047255 1.57763 2002-03 0.044856 1.65173 2003-04 0.044481 1.98879 2004-05 0.048206 2.16598 2005-06 0.050272 2.06508 0.041000 0.042000 0.043000 0.044000 0.045000 0.046000 0.047000 0.048000 0.049000 0.050000 0.051000 20022003200420052006 Fiscal YearsGini Gini Coefficient with Non-Program-Costed Weighted SPDA-Adjusted Performance Predicted Gini Coefficient with Non-Program-Cost Weighted SPDA-Adjusted Performance Figure 4-21. Gini coefficient for non-program-costweighted operating funds per FTE for Florida community colleges with special populat ion demographics adjustment index performance funds included for years 2001-02 through 2005-06.

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132 Table 4-31. Spearmans rho correlation statistics for Measure II before and after for special population demographic adjustment index performance funds. Before SPDA After SPDA Year Spearmans rho Sig. Spearmans rho Sig 2001-02 .808** .000 .766** .000 2002-03 .832** .000 .777** .000 2003-04 .836** .000 .718** .000 2004-05 .814** .000 .755** .000 2005-06 .837** .000 .784** .000 **. Correlation is significant at the 0.01 level (2-Tailed)

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133 Table 4-32. Weighted black male and ESL/EN S degree completers for Florida community colleges for years 2000-01, 2001-02, 2002-03, 2003-04 for performance fund distributions in years 2002, 2003, 2004, 2005, 2006, respectively. Colleges 2002200320042005200620022003200420052006 B revar d 18 19 27 35 31 2 8 0 1 0 B rowar d 91 94 115 138 144 108 152 164 210 294 C entra l Fl or ida 5 9 11 9 12 1 0 0 0 1 Chi po l a 7 7 14 10 8 0 0 0 0 0 D aytona B eac h 21 18 14 33 29 7 10 14 17 8 Edi son 19 24 24 17 25 2 3 9 4 3 Fl a. CC@J ax 80 61 79 71 73 59 49 56 63 71 Fl or id a K eys 2 0 0 0 1 0 0 0 0 1 G u lf C oast 5 10 6 14 14 0 0 2 0 0 Hill s b oroug h 37 58 70 55 77 42 48 39 39 29 I n di an Ri ve r 14 19 10 24 27 2 3 0 2 2 L a k e Ci ty 1 1 1 3 1 0 0 0 0 0 L a k eS umte r 3 1 3 4 4 0 0 0 0 0 M anatee 10 8 11 15 16 3 2 4 1 1 Mi am i D a d e 213 248 219 227 234 226 303 252 282 256 N ort h Fl or ida 3 2 3 0 2 0 0 0 0 0 Ok a l oosaW a l ton 12 20 46 22 16 0 0 0 0 0 P a l m B eac h 74 73 74 95 89 7 14 49 71 93 P ascoH ernan d o 2 1 5 5 2 0 0 0 0 0 P ensaco l a 27 23 19 25 24 0 0 0 0 0 P o lk 11 15 12 13 21 0 0 0 4 1 S anta F e 26 37 29 37 40 60 70 84 97 87 S em i no l e 15 15 25 15 32 8 13 15 24 18 S out h Fl or ida 3 4 1 7 4 0 0 0 0 0 S t. J o h ns Ri ve r 4 2 5 5 2 0 0 0 0 0 S t. P eters b urg 29 29 28 28 29 46 48 59 46 42 T a ll a h assee 89 102 91 127 145 1 2 13 12 11 V a l enc i a 67 90 92 89 95 153 170 199 166 115 Totals:8889901,0341,1231,1977278959591,0391,033 Black MalesESL / ENS Sources: 1) http://www.fccsfinance.org/C10/We ighted%20Com pleters/default.aspx Last Accessed August 21, 2007 2) Pat Windham, PhD., Florida Departme nt of Education, December 7, 2006.

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134 Table 4-33. Special population de mographics adjustment indexe s by Florida community college for years 2002, 2003, 2004, 2005, and 2006. Colleges 2002200320042005200620022003200420052006 Brevard 12.5114.3318.366.6320.025.5514.881.001.921.00 Broward 7.187.958.702.9710.5920.6821.028.4734.3459.22 Central Florida4.198.078.952.069.313.141.001.001.002.40 Chipola 6.707.0512.982.647.160.001.001.001.001.00 Daytona Beach12.7211.878.105.2215.6912.8312.355.9221.8212.09 Ediso n 8.9212.6111.042.1910.731.001.001.001.341.20 Fla. CC@Jax10.418.379.722.468.63102.8056.2221.3073.5794.86 Florida Keys12.241.001.001.006.611.001.001.001.004.91 Gulf Coast6.0313.117.074.7215.741.001.006.651.001.00 Hillsborough6.6711.4812.342.7112.8013.1710.633.089.758.81 Indian River7.7311.445.343.6013.403.023.011.002.032.39 Lake City1.001.061.000.871.001.001.001.001.001.00 Lake-Sumter2.871.002.671.003.401.001.001.001.001.00 Manatee8.077.058.733.4012.444.491.991.321.001.18 Miami Dade12.6917.1514.194.2715.489.339.393.0611.0712.85 North Florida2.581.822.480.001.671.001.001.001.001.00 Okaloosa-Walton15.3126.9156.777.6119.141.001.001.001.000.00 Palm Beach12.2312.8711.964.3013.752.593.724.7121.8735.44 Pasco-Hernando4.422.4210.262.693.501.001.001.001.001.00 Pensacola11.119.957.693.029.941.001.001.001.001.00 Polk4.806.995.041.558.401.001.001.003.491.00 Santa Fe13.5419.9214.225.1019.08117.22179.9175.30258.08283.08 Seminole10.8312.0417.772.9921.5336.6612.014.8524.3622.25 South Florida4.817.131.623.316.681.001.001.001.001.00 St. Johns River3.982.114.621.301.761.001.001.001.001.00 St. Petersburg10.0110.869.322.639.3860.8444.7919.7047.3053.12 Tallahassee24.5929.3123.249.1035.754.275.9213.6637.9242.78 Valencia9.2513.6612.333.3411.9036.1827.5411.081.0023.76 Black Males ESL / ENS

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135 Table 4-34. Measure II performance fund dist ributions before and after special population demographics adjustments by Florida co mmunity college for years 2002, 2003 and 2004. Colleges BeforeAfterBeforeAfterBeforeAfter Brevard 57,088 $ 26,724 $ 49,096 $ 25,352 $ 50,738 $ 36,523 $ Broward 111,769 $ 110,160 $ 98,137 $ 111,562 $ 103,853 $ 105,063 $ Central Florida28,613 $ 11,088 $ 21,226 $ 9,036 $ 20,782 $ 12,205 $ Chipola 9,904 $ 4,697 $ 8,389 $ 3,924 $ 9,341 $ 8,866 $ Daytona Beach42,988 $ 24,367 $ 44,254 $ 22,460 $ 42,779 $ 24,812 $ Edison 31,570 $ 15,568 $ 41,439 $ 20,810 $ 38,137 $ 24,518 $ Fla. CC@Jax103,171 $ 210,953 $ 75,221 $ 92,114 $ 78,816 $ 85,635 $ Florida Keys 3,577 $ 1,902 $ 3,040 $ 1,107 $ 1,713 $ 816 $ Gulf Coast 26,274 $ 10,399 $ 21,226 $ 10,214 $ 20,505 $ 11,027 $ Hillsborough 67,130 $ 43,351 $ 63,904 $ 45,213 $ 62,566 $ 52,848 $ Indian Rive r 29,438 $ 13,442 $ 24,661 $ 13,175 $ 21,445 $ 11,362 $ Lake Cit y 6,603 $ 2,452 $ 6,813 $ 2,483 $ 5,140 $ 2,449 $ Lake-Sumte r 7,772 $ 3,030 $ 7,488 $ 2,727 $ 3,648 $ 1,870 $ Manatee 36,454 $ 15,611 $ 36,316 $ 14,260 $ 34,986 $ 18,944 $ Miami Dade 217,074 $ 192,308 $ 235,798 $ 220,192 $ 212,403 $ 190,905 $ North Florida 3,301 $ 1,347 $ 3,941 $ 1,469 $ 3,703 $ 1,881 $ Okaloosa-Walton31,227 $ 15,984 $ 24,098 $ 19,405 $ 24,429 $ 79,203 $ Palm Beach 66,717 $ 46,283 $ 63,848 $ 41,802 $ 72,183 $ 60,535 $ Pasco-Hernando21,872 $ 8,297 $ 19,650 $ 7,186 $ 21,721 $ 11,570 $ Pensacola 42,231 $ 22,657 $ 37,442 $ 17,857 $ 37,418 $ 21,174 $ Polk 21,735 $ 9,140 $ 20,494 $ 9,309 $ 21,721 $ 11,627 $ Santa Fe 67,612 $ 211,540 $ 68,859 $ 296,267 $ 66,822 $ 206,295 $ Seminole 31,777 $ 22,853 $ 27,026 $ 16,177 $ 34,931 $ 29,205 $ South Florida 13,275 $ 5,222 $ 10,529 $ 4,338 $ 8,899 $ 4,256 $ St. Johns Rive r 20,565 $ 7,942 $ 17,229 $ 6,321 $ 17,079 $ 8,614 $ St. Petersburg104,616 $ 115,835 $ 88,847 $ 81,335 $ 83,237 $ 74,861 $ Tallahassee 79,923 $ 83,383 $ 75,503 $ 86,919 $ 75,610 $ 93,665 $ Valencia 165,212 $ 212,954 $ 164,237 $ 175,699 $ 184,106 $ 167,982 $ Totals:1,449,488 $ 1,449,488 $ 1,358,711 $ 1,358,711 $ 1,358,711 $ 1,358,711 $ 2002 2003 2004

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136 Table 4-35. Measure II performance fund dist ributions before and after special population demographics adjustments by Florida co mmunity college for years 2005 and 2006. Colleges BeforeAfte r BeforeAfte r Brevar d 54,498 $ 23,011 $ 46,631 $ Broward 103,987 $ 168,383 $ 247,521 $ 534,225 $ Central Florida21,455 $ 7,826 $ 42,946 $ 14,197 $ Chipola 8,602 $ 3,365 $ 17,141 $ 5,890 $ Daytona Beach37,749 $ 22,366 $ 83,097 $ 35,524 $ Edison 26,364 $ 9,795 $ 66,701 $ 24,237 $ Fla. CC@Jax 71,146 $ 109,769 $ 152,779 $ 223,790 $ Florida Keys 2,125 $ 758 $ 5,589 $ 1,756 $ Gulf Coast 21,000 $ 8,431 $ 40,244 $ 16,121 $ Hillsborough 65,175 $ 31,103 $ 118,590 $ 60,806 $ Indian Rive r 23,378 $ 9,502 $ 53,286 $ 22,971 $ Lake City 6,275 $ 2,231 $ 14,253 $ 3,864 $ Lake-Sumte r 12,246 $ 4,368 $ 16,396 $ 4,688 $ Manatee 38,457 $ 14,368 $ 77,694 $ 25,689 $ Miami Dade 226,089 $ 145,304 $ 459,552 $ 286,745 $ North Florida 4,807 $ 1,715 $ 10,806 $ 2,964 $ Okaloosa-Walton21,658 $ 10,350 $ 41,921 $ 18,695 $ Palm Beach 72,715 $ 58,349 $ 149,146 $ 149,962 $ Pasco-Hernando21,202 $ 7,715 $ 46,113 $ 12,627 $ Pensacola 42,657 $ 16,127 $ 70,614 $ 24,559 $ Polk 20,646 $ 7,674 $ 41,269 $ 15,112 $ Santa Fe 70,286 $ 477,899 $ 132,471 $ 673,933 $ Seminole 32,233 $ 22,153 $ 72,570 $ 45,925 $ South Florida 7,287 $ 2,891 $ 16,489 $ 5,044 $ St. Johns Rive r 15,990 $ 5,731 $ 28,041 $ 7,640 $ St. Petersburg 87,086 $ 70,327 $ 149,891 $ 102,052 $ Tallahassee 81,115 $ 55,494 $ 170,945 $ 185,191 $ Valencia 162,483 $ 61,707 $ 274,257 $ 166,585 $ Totals:1,358,711 $ 1,358,711 $ 2,600,322$ 2,717,422 $ 2006 2005

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137 Table 4-36. Measure II performance and tota l performance fund distributions after special population demographics adjustments by Florida community college for years 2002, 2003 and 2004. Colleges Measure II After SPDA Total Performance Funds After SPDA Measure II After SPDA Total Performance Funds After SPDA Measure II After SPDA Total Performance Funds After SPDA Brevard57,088 $ 350,334 $ 49,096 $ 321,756 $ 50,738 $ 331,646 $ Broward 111,769 $ 538,619 $ 98,137 $ 551,045 $ 103,853 $ 583,100 $ Central Florida28,613 $ 139,014 $ 21,226 $ 111,927 $ 20,782 $ 121,030 $ Chipola 9,904 $ 54,217 $ 8,389 $ 59,349 $ 9,341 $ 60,721 $ Daytona Beach42,988 $ 234,597 $ 44,254 $ 231,082 $ 42,779 $ 230,564 $ Edison 31,570 $ 198,630 $ 41,439 $ 254,286 $ 38,137 $ 259,070 $ Fla. CC@Jax103,171 $ 630,110 $ 75,221 $ 458,262 $ 78,816 $ 442,316 $ Florida Keys 3,577 $ 19,513 $ 3,040 $ 16,250 $ 1,713 $ 15,971 $ Gulf Coast 26,274 $ 119,105 $ 21,226 $ 123,167 $ 20,505 $ 120,226 $ Hillsborough 67,130 $ 332,134 $ 63,904 $ 355,916 $ 62,566 $ 372,920 $ Indian Rive r 29,438 $ 186,827 $ 24,661 $ 186,034 $ 21,445 $ 179,453 $ Lake Cit y 6,603 $ 45,511 $ 6,813 $ 39,181 $ 5,140 $ 35,707 $ Lake-Sumte r 7,772 $ 49,181 $ 7,488 $ 51,861 $ 3,648 $ 45,093 $ Manatee 36,454 $ 166,159 $ 36,316 $ 179,042 $ 34,986 $ 169,807 $ Miami Dade 217,074 $ 989,261 $ 235,798 $ 1,057,232 $ 212,403 $ 957,828 $ North Florida 3,301 $ 27,689 $ 3,941 $ 28,627 $ 3,703 $ 26,012 $ Okaloosa-Walton31,227 $ 170,834 $ 24,098 $ 163,308 $ 24,429 $ 218,428 $ Palm Beach 66,717 $ 414,578 $ 63,848 $ 423,580 $ 72,183 $ 420,647 $ Pasco-Hernando21,872 $ 109,115 $ 19,650 $ 103,594 $ 21,721 $ 116,936 $ Pensacola 42,231 $ 231,420 $ 37,442 $ 207,334 $ 37,418 $ 226,662 $ Polk 21,735 $ 136,949 $ 20,494 $ 133,916 $ 21,721 $ 146,670 $ Santa Fe 67,612 $ 261,030 $ 68,859 $ 632,190 $ 66,822 $ 534,549 $ Seminole 31,777 $ 527,088 $ 27,026 $ 148,916 $ 34,931 $ 178,293 $ South Florida 13,275 $ 377,956 $ 10,529 $ 47,085 $ 8,899 $ 46,684 $ St. Johns Rive r 20,565 $ 153,486 $ 17,229 $ 92,004 $ 17,079 $ 97,538 $ St. Petersburg104,616 $ 71,030 $ 88,847 $ 494,245 $ 83,237 $ 474,582 $ Tallahassee 79,923 $ 374,721 $ 75,503 $ 387,138 $ 75,610 $ 408,474 $ Valencia 165,212 $ 765,264 $ 164,237 $ 816,046 $ 184,106 $ 853,444 $ Totals:1,449,488 $ 7,674,371 $ 1,358,711 $ 7,674,371 $ 1,358,711 $ 7,674,371 $ 2002 2003 2004

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138 Table 4-37. Measure II performance and total performance fund distributions after special population demographics adjustments by Fl orida community college for years 2005 and 2006. Colleges Measure II After SPDA Total Performance Funds After SPDA Measure II After SPDA Total Performance Funds After SPDA Brevar d 54,498 $ 316,227 $ 117,100 $ 742,634 $ Browar d 103,987 $ 683,259 $ 247,521 $ 1,784,553 $ Central Florid a 21,455 $ 108,154 $ 42,946 $ 261,194 $ Chipola8,602 $ 51,225 $ 17,141 $ 117,302 $ Daytona Beach37,749 $ 206,285 $ 83,097 $ 642,552 $ Edison26,364 $ 182,875 $ 66,701 $ 402,741 $ Fla. CC@Jax71,146 $ 484,407 $ 152,779 $ 1,314,126 $ Florida Keys2,125 $ 13,996 $ 5,589 $ 45,979 $ Gulf Coast21,000 $ 117,390 $ 40,244 $ 280,193 $ Hillsborough65,175 $ 366,792 $ 118,590 $ 860,569 $ Indian Rive r 23,378 $ 173,034 $ 53,286 $ 674,519 $ Lake City6,275 $ 36,276 $ 14,253 $ 163,323 $ Lake-Sumte r 12,246 $ 64,854 $ 16,396 $ 117,184 $ Manatee38,457 $ 173,526 $ 77,694 $ 345,827 $ Miami Dade226,089 $ 905,024 $ 459,552 $ 2,191,030 $ North Florida4,807 $ 28,153 $ 10,806 $ 56,780 $ Okaloosa-Walton21,658 $ 149,571 $ 41,921 $ 332,718 $ Palm Beach72,715 $ 450,905 $ 149,146 $ 966,862 $ Pasco-Hernando21,202 $ 110,767 $ 46,113 $ 362,977 $ Pensacol a 42,657 $ 223,414 $ 70,614 $ 564,664 $ Polk20,646 $ 133,126 $ 41,269 $ 282,894 $ Santa Fe70,286 $ 813,556 $ 132,471 $ 1,383,145 $ Seminole32,233 $ 184,361 $ 72,570 $ 680,221 $ South Florida7,287 $ 42,413 $ 16,489 $ 150,814 $ St. Johns Rive r 15,990 $ 93,023 $ 28,041 $ 206,972 $ St. Petersburg87,086 $ 438,295 $ 149,891 $ 940,658 $ Tallahassee81,115 $ 366,059 $ 170,945 $ 640,041 $ Valencia162,483 $ 757,405 $ 274,257 $ 1,563,525 $ Totals:1,358,711 $ 7,674,371 $ 2,717,422 $ 18,075,996 $ 2006 2005

PAGE 139

139 02 Black Males & Hispanics in Service Area1200000 1000000 800000 600000 400000 200000 0 Frequency25 20 15 10 5 0 Figure 4-22. Descriptive statis tics frequency histogram for black males and Hispanics in respective college service areas for year 2001-02. Colleges2827262524232221201918171615 1413121110 987654321 Mean of 02 Black Males & Hispanics in Service Area1200000 1000000 800000 600000 400000 200000 0 Figure 4-23. One-way ANOVA mean plot for black males and Hispanics in respective college service areas for year 2001-02.

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140 06 Black Males & Hispanics in Service Area1200000.00 1000000.00 800000.00 600000.00 400000.00 200000.00 0.00 Frequency25 20 15 10 5 0 Figure 4-24. Descriptive statis tics frequency histogram for black males and Hispanics in respective college service areas for year 2005-06. Colleges282726 25 242322212019181716151413121110 987654321 Mean of 06 Black Males & Hispanics in Service Area1200000.00 1000000.00 800000.00 600000.00 400000.00 200000.00 0.00 Figure 4-25. One-way ANOVA mean plot for black males and Hispanics in respective college service areas for year 2005-06.

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141 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0% 2 0 % 3 0 % 4 0 % 5 0% 6 0% 7 0% 8 0% 9 0% 1 00 %Cum % of FTECum % of Reven u Perfect Equity with performance without performance Figure 4-26. Lorenz curve 2001-2002 for Flor ida community colleges with program-costweighted operating funds with and w ithout performance funds included.

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142 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 30 % 40 % 5 0 % 6 0 % 7 0 % 80 % 9 0 % 10 0%Cum % of FTECum % of Revenu Perfect Equity with performance without performance Figure 4-27. Lorenz curve 2002-2003 for Florid a community colleges with program-costweighted operating funds per FTE with a nd without performance funds included.

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143 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0% 2 0% 3 0% 4 0% 5 0% 6 0% 7 0% 8 0% 9 0% 1 00 %Cum % of FTECum % of Reven u Perfect Equity with performance without performance Figure 4-28. Lorenz curve 2003-2004 for Flor ida community colleges with program-costweighted operating funds per FTE with and without performance funds included.

PAGE 144

144 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0% 3 0% 4 0% 5 0 % 6 0% 7 0% 8 0 % 9 0% 1 00 %Cum % of FTECum % of Reven u Perfect Equity with performance without performance Figure 4-29. Lorenz curve 2004-2005 for Florid a community colleges with program-costweighted operating funds per FTE with a nd without performance funds included.

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145 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0% 2 0% 3 0% 4 0% 5 0% 6 0% 7 0% 8 0% 9 0% 1 00 %Cum % of FTECum % of Revenu e Perfect Equity with performance without performance Figure 4-30. Lorenz curve 2005-2006 for Florid a community colleges with program-costweighted operating funds per FTE with a nd without performance funds included.

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146 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 3 0 % 4 0 % 5 0 % 6 0 % 7 0 % 8 0 % 9 0 % 1 0 0 %Cum % of FTECum % of Revenu e Perfect Equity with performance without performance Figure 4-31. Lorenz curve 2001-2002 for Flor ida community colleges with non-program-costweighted operating funds per FTE with a nd without performance funds included.

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147 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0% 2 0% 3 0% 4 0% 5 0% 6 0% 7 0% 8 0% 9 0% 1 00 %Cum % of FTECum % of Reven u Perfect Equity with performance without performance Figure 4-32. Lorenz curve 2002-2003 for Florid a community colleges with non-program-costweighted operating funds per FTE with a nd without performance funds included.

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148 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 3 0 % 4 0 % 5 0 % 6 0 % 7 0 % 8 0 % 9 0 % 1 0 0 %Cum % of FTECum % of Revenu e Perfect Equity with performance without performance Figure 4-33. Lorenz curve 2003-2004 for Florid a community colleges with non-program-costweighted operating funds per FTE with a nd without performance funds included.

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149 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 3 0 % 4 0 % 5 0 % 6 0 % 7 0 % 8 0 % 9 0 % 1 00 %Cum % of FTECum % of Revenu e Perfect Equity with performance without performance Figure 4-34. Lorenz curve 2004-2005 for Florid a community colleges with non-program-costweighted operating funds per FTE with a nd without performance funds included.

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150 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 3 0 % 4 0 % 5 0 % 6 0 % 7 0 % 8 0 % 9 0 % 1 0 0 %Cum % of FTECum % of Revenu e Perfect Equity with performance without performance Figure 4-35. Lorenz curve 2005-2006 for Florid a community colleges with non-program-costweighted operating funds per FTE with a nd without performance funds included.

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151 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 3 0 % 4 0 % 5 0 % 6 0 % 7 0 % 8 0 % 9 0 % 1 0 0 %Cum % of FTECum % of Revenu e Perfect Equity with SDPA-Adjusted performance with Non-SPDA-Adjusted performance Figure 4-36. Lorenz curve 2001-2002 for Florid a community colleges with program-costweighted operating funds per FTE with special population demographic adjusted and non-special population demographic adju sted performance funds included.

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152 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0% 2 0% 3 0% 4 0% 5 0% 6 0% 7 0 % 8 0% 9 0% 1 0 0 %Cum % of FTECum % of Reven u Perfect Equity with SPDA-Adjusted performance with Non-SPDA-Adjusted performance Figure 4-37. Lorenz curve 2002-2003 for Florid a community colleges with program-costweighted operating funds per FTE with special population demographic adjusted and non-special population demographic adju sted performance funds included.

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153 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 3 0 % 4 0 % 5 0 % 6 0 % 7 0 % 8 0 % 9 0 % 1 0 0 %Cum % of FTECum % of Revenu e Perfect Equity with SPDA-Adjusted performance with Non-SPDA-Adjusted performance Figure 4-38. Lorenz curve 2003-2004 for Florid a community colleges with program-cost weighted operating funds per FTE with special population demographic adjusted and non-special population demographic adju sted performance funds included.

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154 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0% 2 0% 3 0 % 4 0 % 5 0 % 6 0% 7 0% 8 0 % 9 0 % 1 0 0 %Cum % of FTECum % of Revenu e Perfect Equity with SPDA-Adjusted performance with Non-SPDA-Adjusted performance Figure 4-39. Lorenz curve 2004-2005 for Florid a community colleges with program-costweighted operating funds per FTE with special population demographic adjusted and non-special population demographic ad justed operating performance funds included.

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155 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%0 % 1 0 % 2 0 % 3 0 % 4 0 % 5 0 % 6 0% 7 0% 8 0% 9 0 % 1 0 0 %Cum % of FTECum % of Revenu Perfect Equity with SPDA-Adjusted performance with Non-SPDA-Adjusted performance Figure 4-40. Lorenz curve 2005-2006 for Florid a community colleges with program-costweighted operating funds per FTE with special population demographic adjusted and non-special population demographic ad justed operating performance funds included.

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156 CHAPTER 5 DISCUSSION, OBSERVATIONS, CONCLUSIONS In this study horizon tal fiscal equity has b een examined in literature and in the Florida Community College System (FCCS) for the five -year period of 2001-02 through 2005-06. In this chapter 5 a discussion of results, observations, suggestions for futu re research, and implications for community college administrators will conclude this study. Discussion of Results and Observations Research Question One Performance Included Research question one centered on discerning whether horizontal fiscal equity in perstudent FTE funding distributions to the Florida Community Colleges improved, worsened, or remained unchanged over the five years 2001-02 through 2005-06. Yancey (2002) found decreasing equity with performan ce funds included for three of th e six statistical tests for years 1995-96 through 2000-01; with no changes found when using coefficient of variation, McLoone Index, and Gini coefficient tests (Yancey, Table 5-1). Brown (1999) found decreasing equity with performance funds included for each of the six statistical tests for the first year performance funds were implemented in 1995-96 (Brown, Table 4-8). In this 2007 study, each of the statistics tests found decreasing equity with performance funding included (Table 5-1). ANOVA regression statistics found significant regression equations for three of the equity statistics tests; restricted rang e, McLoone Index, and Gini with academic-program-cost weighted performance included (Table 5-1). The three significant regression statistics ar e important because th e decreasing equity for the 2001-02 thorough 200506 study period is statistically more conclu sive than for the 1995-06 through 2000-01 study period (Yancey, Table 5-1). This finding is not unexpected as there has been much funding policy attention focused on perceived inequity in per-student FTE revenues in Florida

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157 community colleges since 2005 leading to a compression / equali zation funding policy beginning in fiscal year 2005-2006 (Florida Association of Community Colleges, Council of Presidents Report, 2005a, 2005b). This finding of decreasing equity for the 2001-02 thorough 2005-06 study period confirms statistically the decrea sing equity in the per-student revenue distributions. Examining skewness of the per-student FTE revenue distributions for the study period reveals a consistent and informative tr end among the equity statistics tests Range skewness is positive for year 2001-02 indicating outlier per-student FTE revenue at the higher range values (Table 4-7) Range skewness reverses towards outlier per-student FTE revenue at the lower range values in 2002-03 and continued thorough 2005-06 with the largest skew value towards lower range values in 2004-05. Negative range skewness improved some in 2005-06 the year that compression / equalization funding policy, aimed at closing the equity gap for colleges at the low end of the per-student FTE reve nue distribution, was formulated. The skewness trend for restricted range (Table 4.9) was different; negative in 2001-02 (compared to positive for the range) and then continued negative throughout the remaining years of the study as did the range sta tistic. Skewness for coefficient of variation, McLoone index, and Gini with weighted performance funds included al so followed the same trend as for the range positive in 2001-02 and negative for the remaining years of the study (Tables 4-13, 4-15, 4-17). Skewness for Gini with non-program wei ghted performance included was positive throughout the study (Table 4-19). This confirms the need and methodology for weighting FTE to equalize for cost variations in the various college service areas The slope trend for Gini with non-program weighted performance included does fo llow the same increase / decrease pattern as

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158 all other statistics; peaking in 2004-05 and show ing some improvement in 2005-06 the first year of compression / equalization funding policy implementation. The skewness results focus attention on colleges at the lower end of the per-student FTE revenue distributions. Examining the colleges in the lower quartile (lowest seven colleges) the data indicate show colleges in the lower quartile vary from year to year, and by whether the perstudent FTE revenue is academic-progr am-cost-weighted or non-weighted (Tables 5.2, 5.3). The year-to-year pattern of colleges in the lowest quartile is consiste nt for the range, coefficient of variation, McLoone Index, and Gini statistics tests, but vary by whether per-student FTE revenue is measured by academic-program-cost-weighted or non-weighted. Comparing Tables 5.2 and 5.3, it can be seen that several colleges ar e represented in each table, some are represented in Table 5.2 only, and others ar e in Table 5.3 only. From a horizontal equity perspective, Ta ble 5.2 reflects the per-student F TE revenue distribution that has been weighted to level the equity analysis play ing field. Yancey (2002) describes the Table 5.2 analysis as an analysis of as equitable opera ting funds (Yancey, p.108). This implies that perstudent FTE revenue for colleges in Table 5.2 has been weighted to refl ect differing costs of operating, but they are still in the lower per-stu dent FTE revenue quartile. The following colleges appear in both Table 5.2 and Table 5.3: Hi llsborough, Indian River, Miami Dade, OkaloosaWalton, Pasco-Hernando, South Florida, and Tallah assee. These colleges would appear to have inequitable per-student FTE re venue funding whether measuring weighted or non-weighted operating funds when performance funds are included. Research Question One Performance Excluded With performance funds excluded, the ANOV A regression statisti cs found a significant regression equation for only one of the equity statistics tests; Gi ni with academic-program-cost weighted performance excluded (Table 5-4). This significant Gini re sult, along with all other

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159 equity tests except the Federal ra nge ratio, indicates decreasing equity with performance funds excluded. Interesting to note how ever is the Federal range ratio test result which indicated increasing equity for the five years 2001-02 through 2005-06. Although ANOVA regression for the Federal range ratio was not found significant at 95% confidence, it is somewhat significant that it is the first finding of in creasing equity for the system, and it is found with performance funds excluded. It is also significant that for the range, Federal range ra tio, McLoone and Gini with program-cost-weighted per-student FTE reve nue the values were lower with performance funds excluded than for performance funds includ ed. These two results confirm to some degree that policymakers should assess equity with performance funding excluded until suitable methods are found and corresponding funding polic y implemented to improve per-student FTE revenue equity with performance funding included. Examining skewness of the per-student FTE revenue distributions with performance funds excluded (Tables 4-3, 4-8, 4-14, 4-16, and 4-18) for the study period reveals the same consistent trend among five of th e equity statistics tests with performance excluded as with performance included. That is, positive skewne ss in 2001-02 reversing to negative skewness for years 2002-03 through 2005-06. The skewness with performance funds excluded reached peak negative in 2004-05, and then improved some in 2005-06 same as for skewness with performance funds included (Tables 4-1, 4-7, 4-13, 4-15, and 4-17) Skewness trend for restricted ra nge with performance excluded (Table 4.4) was again different; negative in 2001-02 (compared to positive for the range) and then continuing negative throughout the remaining years of th e study as did the range statistic. Skewness for Gini with non-program weighted performance ex cluded was positive throughout the study (Table 4-20)

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160 followed the same pattern as with performance included; peaking in 2004-05 and showing some improvement in 2005-06. It is very apparent from the skewness an alysis for both per-student FTE revenue with performance included and performance excluded that negative skewness peaked in 2004-05 followed by some improvement in 2005-06. This pattern was consistent for all six equity statistics measures in this study. This consistent skewness result is believed to be related to two separate funding policies implemented in 2004-05 and 2005-06; namely capac ity restoration in 2004-05 and funding formula-driven equalizatio n in 2005-06. These funding policies will be discussed more fully later in this chapter. Examining the colleges in the lower quartile with performance excl uded, the data again indicate that colleges in the lower quartile vary from year to year, and by whether the per-student FTE revenue is academic-program-cost-weighted or non-weighted (Tables 5.5, 5.6). The yearto-year pattern of colleges in the lowest quartil e is consistent for the range, coefficient of variation, McLoone Index, and Gini statistics tests, but vary by whether per-student FTE revenue is measured by academic-program-cost-weighted or non-weighted. In conclusion to research question one, the si x statistics for measuring horizontal equity in the Florida community college system for years 2001-02 through 2005-06 indicated that equity with performance included decreased. Al though there were one-to-two years where equity did increased with performance included, the ANOVA Regression conclusive at confidence level of 95% for the restricted range, McLoone index, and Gini (Table 5.1) indicated the prevailing trend was a decrease in equity when measur ing with performance funds included. With performance funding excluded, five of the statis tic measures indicated decreasing equity while the Federal range ratio indicated increas ing equity with performance excluded (Table 5.4). It is

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161 noted again also that (a) the Federal range ratio finding of increasing e quity with performance excluded is the first such finding of increasi ng equity for the system, and it is found with performance funds excluded, and (b) the values fo r Federal range ratio, McLoone, and Gini with program cost weighted performance excluded were lower than for the corresponding values with performance funds included. Research Question Two SPDA-Performance Included With SPDA-performance funds included, the ANOVA regression statistics found significant regression equations for th ree of the equity statistics te sts; restricted range, federal range ratio, and Gini with academic-progr am-cost weighted performance included (Table 5-7). These significant regressi on results at 95% confiden ce, along with all other e quity tests, indicate decreasing equity with SPDA-performance funds included. It is important to note that al l equity values for restrict ed range with SPDA-performance included (Table 4-25) are lower than the corresponding values with non-SPDA-performance included (Table 4-9). Similarly, values for the federa l range ratio with SPDA-performance included (Table 4-26) were lower four of five years; coefficient of variation with SPDAperformance three of five years were lower (Table 4-27); and Gini with program-cost weighted SPDA-performance (Table 4-29) were lower three of five years when compared to corresponding values with non-SPDA-performance included (Tables 4-11, 4-13, 4-17). Examining skewness of the per-student FTE revenue distributions with SPDAperformance funds included (Table 4-21) for the study period reveals the same consistent trend among five of the equity statistics tests with SPDA-performance excluded as with non-SPDAperformance included. That is, positive skewne ss in 2001-02 reversing to negative skewness for years 2002-03 through 2005-06. Also consiste nt, skewness with SPDA-performance funds included reached its peak negative in 2004-05, a nd then improved some in 2005-06 same as for

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162 skewness with non-SPDA-performance funds included (Table 4-1) Skewness for Restricted Range with SPDA-performance wa s also negative through the study same as for skewness with non-SPDA-performance funds included. Skewness for the non-program-cost weighted SPDAperformance followed the same patterns. The implications of the mostly negative skewness are outliers of colleges at the lower end of th e per-student FTE revenue distribution. Interesting however, are the following obs ervations. The skewness in 2001-02 and 200203 with SPDA-performance included is more positive and more negative than corresponding skewness with non-SPDA-performance included. The skewness with SPDA-performance funds included were less negative in 2002-03, 2004-05 and 2005-06 than corresponding skewness with non-SPDA-performance included. This suggest s that: (a) the SPDAperformance improved outliers of colleges at the lower end of the per-student FTE reve nue distribution, and (b) outlier colleges at the lower end of the per-student FTE revenue distribution were more effective in serving special populati ons in those years. Examining the colleges in the lower pe r-student FTE revenue quartile with SPDA performance included, the data agai n indicate the colleges in the lower quartile vary from year to year, and by whether the per-student FTE reve nue is academic-program-cost-weighted or nonweighted (Tables 5-8, 5.9). The year-to-year pattern of co lleges in the lowest quartile is consistent for the range, coeffici ent of variation, McLoone Index, and Gini statistics tests, but vary by whether per-student FTE revenue is measured by academic-program-cost-weighted or non-weighted. Assessing the relative positions of colleges in Tables 5.2, 5.5, 5.6, 5.8 and 5.9, one may discern the impacts on colleges in the lower per-student FTE quart ile with performance included, with performance excluded, and with SPDA-perf ormance included. Referencing also Table 4-33

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163 and 4-34, it is evident that Tallahassee (T CC) and Valencia (VCC) community colleges are among the most productive in degree completers for Black Males and Hispanics. TCC in particular is very productive fo r Black males but less so for Hisp anics; as is Okaloosa Walton. VCC is also productive in degree completers fo r Black Males but more so for Hispanics than TCC. By tracing the movements of TCC in Ta bles 5.2 and 5.8 for years 2001-02 and 2002-03, we see that TCC is the 5th lowest per student FTE revenue with non-SPDA-performance included in Table 5.2 and remains 5th lowest per student FTE revenue with SPDA-performance included in Table 5.8 in year 200102 for no change in quartile pos ition. There were no relative changes in TCCs position in the lower per-student FTE revenue quartile for years 2001-02, 2004-05, and 2005-06. For years 2002-03 and 200304, TCCs per-student FTE revenue moved from 6th and 5th lowest in Table 5.2 to 4th lowest in Table 5.8 with SPDA-performance. Aside from the movements as representative by tracing TCCs movements in the lower per-student FTE revenue quartile of the distribution, there were ve ry few changes in the colleges in the lower per-student FTE revenue quart ile when comparing SPDA-performance and nonSPDA-performance included. This can be partia lly explained by the rela tive small Measure II Special Population funds allocated as a percen tage of Total Funds Av ailable in each year (Table 5-10) The very small percentages for Measure II Special Population funds allocated each year would suggest that neither SPDA-performa nce nor non-SPDA-performance would have significant affects on colleges in the lower per-st udent FTE revenue quartile of the distribution. Concluding research question two, the six statistics for measur ing horizontal equity in the Florida community college system for years 2001 -02 through 2005-06 indicated that equity with SPDA-performance included decreased (Table 5.7). Although there were one -to-two years where equity did increased with SPDA-performance in cluded, the ANOVA Regression conclusive at

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164 confidence level of 95% for the restricted range, federal range ration, a nd Gini-weighted (Table 5.7) indicated the prevailing trend was a d ecrease in equity when measuring with SPDAperformance funds included. It is noted again also that the values of the Gini in Table 4-29 are lower than the corresponding values in Table 4-17 for three years 2002-03, 2003-04 and 2004-05 indicating more equity in the distribution when measuring with Gini with program-cost-weighted FTE and with SPDA-performance included. For year 2005 -06, the Gini coefficient value with SPDAperformance funds included was higher than the corresponding value in Table 4-17 indicating a less favorable equity distribution in 2005-06 w ith SPDA-performance fund s included. The fact that equity with SPDA-performance include d suggests more equity than with non-SPDAperformance included does not mean that f unding policy should measure equity with SPDAperformance included. The data do suggest that a special population adju stment method or other similar methods of assessing the effects of pe rformance funding on equity should be considered for further studies. Effects of Capacity Rest oration Funding Policy Capacity restoration is a term used in the Florida Community Colleges System and Florida Legislature to describe the funding policy decision for holding harmless the total funds available to colleges whos FTE was adversel y affected by hurrican es in 2004-05 and 20052006. With the capacity restoration funding policy, the three-year rolling average FTE for each college was adjusted by appropriating FTE-driv en funding to each college based on the highest actual FTE level earned during the three-years of the three-year rolling average. The capacity restoration funding policy has the ef fect of increasing total funds av ailable in the system even as FTE enrollment decreases (Table 5-11). The peaking of skewness in the per-student FTE revenue at both the lower and higher quartiles of the distri butions is believed to be influenced in some

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165 part to the effects of capacity restoration. For the 2008-2009 le gislature appropriation season, a proposal is pending to turn off the capacity restoration funding switch in Funding Model of the Florida Community College System. Effects of Compression / Equalization Funding Policy Compression-Equalization is a term used in the Florida Community Colleges System and Florida Legislature to describe the funding policy decision to clos e the equity gap at the lower end of the per-student FTE revenue distribution. Concerns about in equity in the lower end of the distribution were first voiced publically at the Florida Community Colleges System Council of Presidents Meeting held in March 2005. Much of the concern centered colleges in the lower perstudent FTE revenue quartile, as presented in Table 5.9. Seminole Community College, represented prominently in Table 5.9, expre ssed much concern in the March 2005 Council of Presidents Meeting. It is pointed out here th at inequity discussion and concerns at the March 2005 meeting were centered on both weighted and unweighted per-student FTE revenue distributions. The compression-equalization funding policy was funded for an amount of $10 million by the legislature for the 2006-2007 fiscal years; distributed to colleges below the system-wide average funded per centage of the Funding Model. The consistent pattern of peaking of skewne ss in the per-student FTE revenue distribution in 2004-05 with some improvement in 2005-06 is beli eved to be due at least in part to the recommendations adopted in January 2005 for the 2005-06 funding formula. These recommendations were the beginning of the comp ression-equalization fund ing policy established in October 2005 and funded by the Florida Legi slature in 2006-2007. Th e stated goal of the compression-equalization funding policy is to redu ce the inequity gap from approximately 21% to 5% or less when measured by the range of the funding formula standard.

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166 Areas for Further Research There are several areas of furthe r research that could emanate from this study. The equity affects of compression-equalization fundi ng policy for the years 2006-07 through 2009-2010 would be of value to funding policy makers and higher education administrators. In particular, funding policymakers and administrator would be in terested in the movement of colleges in the lower and upper quartiles of the per-student FT E distributions, and effective the compressionequalization funding policy as been over time. The relative percentage of M easure II special population f unding to total funds available (Table 5.10) is most likely to small to adequately test the equity effect s of indexing performance funding to special populations in the colleges serv ice areas. The examinati on of horizontal fiscal equity changes if all performance funding was in dexed to all degree comp leters and populations of service areas would likely yield better insight into methods by which equity with performance included can be accomplished. The special population demographic adjustment indexes and redistribution of Measure II funds (Tables 4-33, 4-34, 4-35) suggests that colleges in close pr oximity to larger universities are more productive in graduating Black males a nd Hispanic degree completers. Among those colleges are Tallahassee, Valencia, Miami Dade, Florida College at Jacksonville, and Santa Fe community colleges. This could be influenced by the parental influence of Black faculty hired at the larger universities, more opportunities in pr ofessional careers, spor ts opportunities, etc. A study of the cultural, professiona l, entrepreneurial, sports, a nd other influences on graduating Black males and Hispanic of colleges in close prox imity to other larger universities would add a qualitative research dimension to the non-experimental / correl ation design of this study. The six equity statistic s measures are well founded in lite rature, practice and the courts. The Florida Community College System has long held the position the f unding to the community

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167 colleges is not equitable when compared to f unding to the state universities. The research component of funding to the state universities accounts for part of the perceived funding inequity. Controlling for the research com ponent and study of funding equity between the community college system and the state un iversities would shed light on the claim. Just as full employment in the U. S. econom y is impractical; it is equally unlikely that perfect equity, as described by the Lorenz curve, will ever be achieved. This is despite the worthy goal of funding policies such as compression-equalization. It is common in the Florida Community College System to compare per-stud ent FTE funding to other states in the SREB area. A comparative study of horizontal equity in an SREB-benchmark state would aid is setting a perhaps more practical standard for acceptable equity in per student FTE revenue distributions. Implications for Policymakers and College Administrators This study confirms that funding policy makers should continue to assess per-student FTE funding equity based on State support and stude nt fees; prior to the effects of performance funding included in the distribution. The adverse effects of performan ce funding on per-student FTE revenue distributions were proven at a 95 % confidence level in this study for the period 2001-02 through 2005-06. The skewness data suggest that continued in creases in appropria tions and total funds available with declining FTE is likely to cont ribute to outliers in both the lower and upper quartiles of the distributions. Consequently, the study implies th at the pending decision to turn off capacity restoration switch in the funding model would tend to improve funding equity in the distribution. The consistent improvement in the skewne ss data in 2005-06 sugge sts that the funding policy for compression / equalizatio n is contributing to improved equity in the lower quartile of the distributions.

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168 Although results of the equity tests with SPDA-performance included were mixed, there was evidence of improvements in variations in the distributions when measured by the federal range ratio, McLoone index and Gini coefficient. These improvements were observed despite the very small percentage of Meas ure II funds to total funds avai lable. This suggests continued support of exploring other demographically ba sed methods and policie s to achieve improved fiscal equity includi ng the effects of performance funding, and to incentivize improvements in males and minority degree completers. One such study might index total performance funding each year to an education access inde x for the various service areas. Lastly, several colleges were observed as be ing especially productive in graduating Black males and Hispanic degree completers. College ad ministrators who are committed to outreach programs aimed at increasing Black males and Hispanic degree completers will want to explore and share best practices. Implications for Horizontal Equity Theory This study sheds new light on the effects of using weighted full-time-equivalent (FTE) students for the Gini coefficien t and Lorenz Curve horizontal equity measure tests. Although Berne and Stiefel (1984) and other scholars do addr ess (a) critics arguments about the difficulty in interpreting unweighted dispersions measures (p .233) and (b) the fact th at weighted dispersion measures do not always show greater equity th an unweighted dispersion measures (p.238), this study argues that the theoretical literature on their effects on th e Gini coefficient and Lorenz curve are unclear. The results presented in th is study show that the use of weighted and unweighted FTE students in analyses of the Gini coefficient does re sult in different values for the equity coefficient for the Gini coefficient measure. In additi on, this study confirms existing theories on the unstable nature of the range stat istic and the more appropriate use of Spearmans rho correlation for distributions th at are not normally distributed.

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169 Researchers Perspective I conclude this study with a discussion of the practical realities a nd differences between horizontal fiscal equity and funding policy. Calculating, m easuring, analyzing and interpreting horizontal fiscal equity statistics are complex ta sks and processes. The concepts of horizontal fiscal equity, while not rocket science, are also not necessarily intuitive or easily grasped. The calculations themselves are voluminous and prone to error. Berne and Stiefel (1984) points out well that interpretation of results involve many value judgments. It is little wonder that practitioners and policymakers often resort to th e range statistic the si mplest and most often unstable statistic to describe and improve funding inequities. Funding policy is equally challenging. Es tablishing funding policy requires political insight, strong negotiation and in ter-personal skills, and determ ination. Implementing funding policy requires so-called soft skills to empathi ze, care about and feel the pain of others. These skills lead to worthy policies such as holding harmless those colleges whose students and enrollments were affected by hurricanes in 2004-05 and 2005-06. The duties of researchers, analysts and scholars therefore include the examination, discernment and shedding of light on the effect s of funding policy on equal treatment of equals. Such duties also include exploring ways to assist and enlighten funding policies and policymakers. This study has at tempted to assist those duties.

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170 Table 5-1. ANOVA regression of per-student FTE revenue equ ity with performance funds included for Florida community coll eges years 2001-02 through 2005-06. Conclusive at Equity Statistics Tests Equity Trend Found P < .05 Range Decreasing No Restricted Range Decreasing Yes Federal Range Ratio Decreasing No Coefficient of Variation Decreasing No McLoone Index Decreasing Yes Gini Coefficient Weighted Decreasing Yes Gini Coefficient Non-Weighted Decreasing No Table 5-2. Florida community colleges in lower quartile of per-student F TE revenue equity with weighted performance funds includ ed for years 2001-02 through 2005-06. 2001-02 2002-03 2003-04 2004-05 2005-06 Gulf Coast Hillsborough Hillsborough Hillsborough Hillsborough Hillsborough Gulf Coast Gulf Coast Gulf Coast Gulf Coast Miami Dade Miami Dade Miami Dade Pasco-Hernando Tallahassee South Florida Pasco-Hernando PascoHernando Tallahassee Pasco-Hernando Tallahassee South Florida Tallahassee Miami Dade Miami Dade Pasco-Hernando Tallahassee South Flor ida South Florida Indian River Indian Rivers Okaloosa-Walton Okal oosa-Walton Daytona South Florida Table 5-3. Florida community colleges in lower quartile of per-student F TE revenue equity with non-weighted performance funds incl uded for years 2001-02 through 2005-06. 2001-02 2002-03 2003-04 2004-05 2005-06 Seminole Seminole Seminole Tallahassee Tallahassee Indian River Hillsborough Hillsboroug h Pasco-Hernando Pasco-Hernando South Florida Okaloosa-Walton Pasco-Hernando Seminole Hillsborough Valencia South Florida Okaloosa-Walton Hillsborough Seminole Okaloosa-Walton Valencia Miami Da de Miami Dade Indian River St. Johns River Miami Dade Tallahassee Santa Fe Santa Fe Broward Pasco-Hernando Valencia Broward Miami Dade

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171 Table 5-4. ANOVA regression of per-student FTE revenue equ ity with performance funds excluded for Florida community coll eges years 2001-02 through 2005-06. Conclusive at Equity Statistics Tests Equity Trend Found P < .05 Range Decreasing No Restricted Range Decreasing No Federal Range Ratio Increasing No Coefficient of Variation Decreasing No McLoone Index Decreasing No Gini Coefficient Weighted Decreasing Yes Gini Coefficient Non-Weighted Decreasing No Table 5-5. Florida community colleges in lower quartile of per-student F TE revenue equity with weighted performance funds exclud ed for years 2001-02 through 2005-06. 2001-02 2002-03 2003-04 2004-05 2005-06 Gulf Coast Hillsborough Hillsborough Hillsborough Hillsborough Hillsborough Gulf Coast Gulf Coast Gulf Coast Gulf Coast Miami Dade Miami Dade Miami Dade Pasco-Hernando Tallahassee South Florida Pasco-Hernando Pasco-Hernando Tallahassee Pasco-Hernando Tallahassee South Florida Tallahassee Miami Dade Miami Dade Pasco-Hernando Tallahassee South Florida South Florida Indian River Okaloosa-Walton Okaloosa-Walton Okaloosa-Walton Daytona Beach South Florida Table 5-6. Florida community colleges in lower quartile of per-student F TE revenue equity with non-weighted performance funds excl uded for years 2001-02 through 2005-06. 2001-02 2002-03 2003-04 2004-05 2005-06 Seminole Seminole Seminole Tallahassee Tallahassee Indian River Hillsborough Hillsboroug h Pasco-Hernando Pasco-Hernando Valencia Okaloosa-Walton Pasco-Hernando Seminole Hillsborough Okaloosa-Walton Valencia Okaloosa-Walton Hillsborough Seminole South Florida South Florida Tall ahassee Miami Dade Santa Fe St. Johns River Miami Dade Vale ncia Santa Fe Indian River Broward Pasco-Hernando Miami Dade Broward Miami Dade

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172 Table 5-7. ANOVA regression of per-student FTE revenue equ ity with special population demographics adjusted performance Funds included for Florida community colleges years 2001-02 through 2005-06. Conclusive at Equity Statistics Tests Equity Trend Found P < .05 Range Decreasing No Restricted Range Decreasing Yes Federal Range Ratio Decreasing Yes Coefficient of Variation Decreasing No McLoone Index Decreasing No Gini Coefficient Weighted Decreasing Yes Gini Coefficient Non-Weighted Decreasing No Table 5-8. Florida community colleges in lower quartile of per-student F TE revenue equity with weighted special population demographics adjusted performance funds included for years 2001-02 through 2005-06. 2001-02 2002-03 2003-04 2004-05 2005-06 Gulf Coast Hillsborough Hillsborough Hillsborough Hillsborough Hillsborough Gulf Coast Gulf Coast Gulf Coast Gulf Coast Miami Dade Miami Dade Miami Dade Pasco-Hernando Tallahassee South Florida Tallahassee Pasco-He rnando Tallahassee Pasco-Hernando Tallahassee South Florida Tallahassee Miami Dade Miami Dade Pasco-Hernando Okaloosa-Walton OkaloosaWalton Daytona Beach Indian River Indian River Indian River South Fl orida South Florida Daytona Beach Table 5-9. Florida community colleges in lower quartile of per-student F TE revenue equity with non-weighted special populati on demographics adjusted pe rformance funds included for years 2001-02 through 2005-06. 2001-02 2002-03 2003-04 2004-05 2005-06 Seminole Seminole Seminole Tallahassee Tallahassee Indian River Hillsborough Hillsboroug h Pasco-Hernando Pasco-Hernando South Florida Okaloosa-Walton Pasco-Hernando Seminole Hillsborough Valencia South Florida Okaloosa-Walton Hillsborough Seminole Okaloosa-Walton Valencia Miami Da de Miami Dade Indian River Broward Miami Dade Tallahassee Santa Fe Santa Fe St. Johns River Pasco-Hernando Valencia Broward Miami Dade

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173 Table 5-10. Florida community colleges perc entages of performance based budget funds and Measure II special population funds to to tal funds available for years 2001-02 through 2005-06. Year Total Funds Available Total Performance Funding (PBB) % Percent PBB Total Measure II PBB Funding % Percent Measure II to Total Funds Available 2001-021,184,979,617 $ 7,674,371 $ 0.65% 1,449,488 $ 0.12% 2002-031,273,472,971 $ 7,674,371 $ 0.60% 1,358,711 $ 0.11% 2003-041,321,046,529 $ 7,674,371 $ 0.58% 1,358,711 $ 0.10% 2004-051,402,659,976 $ 7,674,371 $ 0.55% 1,358,711 $ 0.10% 2005-061,459,745,003 $ 18,075,996 $ 1.24% 2,717,422 $ 0.19% Table 5-11. FTE growth compared to growth in total funds available to Florida community colleges For Years 2001-02 through 2005-06. Year FTE Non-weighted % Percent FTE Growth Total Funds Available % Percent Growth Total Funds Available 2001-02267,4861,184,979,617 $ 2002-03285,1286.60%1,273,472,971 $ 7.47% 2003-04297,7954.44%1,321,046,529 $ 3.74% 2004-05294,818-1.00%1,402,659,976 $ 6.18% 2005-06287,714-2.41%1,459,745,003 $ 4.07%

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174 APPENDIX. RAW DATA: STATE SUPPORT FU NDING 2001-02 THROUGH 2005-06. Gen.Rev. Lotter y Student WorkforceTotal FundsFTE COLLEGESCCPF CCPF FeesPBBFundingAvailableStudents Brevard $ 18 049 260 $ 3 745 013 $ 12 578 051 $ 380 698 $ 11 142 397 $ 45 895 419 9 575 Broward 31 471 9376 112 63531 291 339540 22816 792 841 86 208 980 20 743 Central Florida6 299 8671 867 3606 942 178156 5397 018 826 22 284 770 4 645 Chi p ola 4 170 999644 0501 813 75859 4242 921 478 9 609 709 1 412 Da y tona Beach15 638 7225 517 87811 436 021253 21818 903 721 51 749 560 12 269 Edison 13 023 5822 295 2958 700 251214 6324 246 188 28 479 948 6 200 Fla. JC @ Ja x 25 670 0919 032 02221 243 275522 32835 892 304 92 360 020 18 931 Florida Ke y s2 709 444411 7021 344 89521 1881 900 104 6 387 333 913 Gulf Coast7 194 6811 606 1135 577 783134 9805 784 877 20 298 434 4 568 Hillsborou g h24 294 7294 846 70019 740 804355 91310 325 471 59 563 617 14 232 Indian River13 007 0874 019 8869 353 007202 82318 348 838 44 931 641 11 241 Lake Cit y 3 301 234972 6172 303 44449 6626 510 018 13 136 975 1 935 Lake-Sumter4 859 340588 8742 500 35353 9231 491 281 9 493 771 1 824 Manatee 10 012 4161 942 1188 767 569187 0024 380 967 25 290 072 5 588 Miami-Dade81 213 75915 358 29871 826 7051 014 02730 495 635 199 908 424 46 985 North Florida2 439 801435 6581 105 45629 6432 254 597 6 265 155 936 OkaIoosa7 740 6181 756 7995 483 913186 0774 398 819 19 566 226 4 818 Palm Beach19 508 7414 231 98020 970 647435 01221 068 605 66 214 985 14 180 Pasco5 782 1651 400 8534 726 564122 6905 940 779 17 973 051 4 128 Pensacola14 683 5273 479 7549 692 770250 99413 333 765 41 440 810 8 609 Polk 7 414 2001 464 3375 767 758149 5444 609 882 19 405 721 4 035 Saint Johns 7 252 9831 023 0843 379 958117 1022 613 274 14 386 401 3 482 Saint 26 218 1844 969 92122 960 065536 01213 633 533 68 317 715 13 277 Santa Fe 13 615 3873 784 41015 737 313386 00911 699 706 45 222 825 10 634 Seminole 8 774 5103 195 67611 423 428166 10915 261 425 38 821 148 10 067 South Florida2 805 4091 213 9832 091 78859 8116 958 844 13 129 835 3 242 Tallahassee16 160 1552 593 00113 030 261371 2613 851 871 36 006 549 8 619 Valencia 31 502 2206 177 48333 089 474717 52211 143 823 82 630 522 20 399 Total $ 424,815,048 $ 94,687,500 $ 364,878,829 $ 7,674,371 $ 292,923,869 $ 1,184,979,617 267,486 2001-02 Funding and FTE Data

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175 Gen.Rev. Lotter y Student WorkforceTotal FundsFTE COLLEGESCCPF CCPF FeesPBBFundingAvailableStudents Brevard $ 19 932 135 $ 3 674 315 $ 13 786 434 $ 345 501 $ 11 422 166 $ 49 160 551 10 305 Broward 37 294 2335 997 24133 826 037537 61916 901 166 94 556 296 22 104 Central Florida7 242 5041 832 1087 262 536124 1187 042 144 23 503 410 4 823 Chi p ola 4 487 263631 8922 073 01763 8142 932 335 10 188 321 1 550 Da y tona Beach18 615 1825 413 71212 343 949252 87618 958 875 55 584 594 12 684 Edison 14 377 4242 251 9659 582 638274 9154 257 167 30 744 109 6 594 Fla. JC @ Ja x 28 111 5658 861 51724 492 122441 36936 691 071 98 597 644 20 139 Florida Ke y s2 984 639403 9301 409 56718 1831 905 017 6 721 336 949 Gulf Coast8 274 0611 575 7935 942 062134 1795 801 746 21 727 841 4 739 Hillsborou g h26 874 1614 755 20521 221 679374 60610 423 780 63 649 431 15 432 Indian River16 171 7723 943 9999 843 484197 52118 408 828 48 565 604 11 365 Lake Cit y 3 376 789954 2562 963 14443 5106 574 102 13 911 801 2 286 Lake-Sumter5 430 728577 7572 821 86256 6221 619 977 10 506 946 2 064 Manatee 11 318 8251 905 4559 458 201201 0985 260 728 28 144 307 6 056 Miami-Dade93 355 36015 068 36673 585 9221 072 83930 821 476 213 903 963 51 352 North Florida2 801 826427 4341 263 90131 0982 274 057 6 798 316 1 004 OkaIoosa8 825 7481 723 6345 897 673168 0034 410 950 21 026 008 5 074 Palm Beach22 944 0434 152 08921 460 111445 62721 125 759 70 127 629 14 983 Pasco6 597 7811 374 4085 499 272116 0585 958 582 19 546 101 4 645 Pensacola16 180 2473 414 06410 072 759226 91713 551 337 43 445 324 8 436 Polk 8 222 7561 436 6936 282 185145 1024 622 834 20 709 570 4 403 Saint Johns 8 298 2181 003 7703 709 521102 9122 622 783 15 737 204 3 556 Saint 29 852 2534 876 09925 694 090501 75713 748 609 74 672 808 14 706 Santa Fe 15 785 9643 712 96816 771 823404 78311 732 137 48 407 675 11 331 Seminole10 956 1603 135 34813 187 303159 76515 449 509 42 888 085 10 991 South Florida3 845 4811 191 0662 373 16053 2767 134 997 14 597 980 3 518 Tallahassee17 861 0252 544 05113 260 212375 7214 144 838 38 185 847 8 925 Valencia 36 483 6726 060 86533 070 781804 58211 444 371 87 864 271 21 116 Total $ 486,501,815 $ 92,900,000 $ 389,155,444 $ 7,674,371 $ 297,241,341 $ 1,273,472,971 285,128 2002-03 Funding and FTE Data

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176 Gen.Rev. Lotter y Student WorkforceTotal FundsFTE COLLEGESCCPF CCPF FeesPBBFundingAvailableStudents Brevard $ 19 830 320 $ 3 674 315 $ 14 380 248 $ 345 861 $ 11 359 959 $ 49 590 703 10 535 Broward37 218 7985 997 24136 759 383581 89016 779 536 97 336 848 22 682 Central Florida7 235 1811 832 1087 521 655129 6077 012 496 23 731 047 4 906 Chi p ola 4 584 024965 2252 265 75861 1962 918 917 10 795 120 1 686 Da y tona Beach18 656 7505 413 71213 894 406248 53118 887 287 57 100 686 13 391 Edison14 433 4072 585 29810 895 897272 6894 218 804 32 406 095 7 242 Fla. JC @ Jax28 016 1678 861 51727 354 849435 49736 567 324 101 235 354 20 613 Florida Ke y s2 970 595403 9301 515 86316 8681 896 436 6 803 692 880 Gulf Coast8 495 0591 575 7936 579 131129 7045 773 268 22 552 955 4 731 Hillsborou g h26 777 1374 755 20524 769 643382 63810 343 178 67 027 801 16 551 Indian River16 149 9183 943 99911 540 845189 53618 346 608 50 170 906 11 975 Lake Cit y 3 347 179954 2563 317 08838 3986 556 011 14 212 932 2 443 Lake-Sumter5 408 708577 7573 082 39046 8711 606 523 10 722 249 2 145 Manatee11 340 1731 905 45510 719 135185 8495 225 567 29 376 179 6 425 Miami-Dade92 918 96315 401 70086 351 119979 32630 543 083 226 194 191 54 393 North Florida2 818 690427 4341 390 59827 8342 265 357 6 929 913 954 OkaIoosa-9 056 4441 723 6346 590 922163 6544 382 860 21 917 514 5 326 Palm Beach23 680 8394 152 08924 287 585432 29521 033 116 73 585 924 15 633 Pasco-6 556 7621 374 4086 262 535127 0875 933 520 20 254 312 4 995 Pensacola16 107 1283 414 06410 734 137242 90613 496 143 43 994 378 8 663 Polk8 179 5201 436 6936 818 300156 7644 596 418 21 187 695 4 669 Saint Johns 8 457 8391 003 7704 248 092106 0032 602 573 16 418 277 3 764 Saint 30 316 5174 876 09929 264 777482 95813 656 499 78 596 850 15 621 Santa Fe15 755 1133 712 96817 991 206395 07611 669 512 49 523 875 11 542 Seminole10 868 1713 135 34815 173 075184 01915 395 750 44 756 363 11 426 South Florida4 115 2781 191 0662 529 84451 3277 116 070 15 003 585 3 475 Tallahassee18 345 8352 544 05114 659 417390 4194 094 976 40 034 698 9 618 Valencia36 301 5586 060 86535 021 294869 56811 333 103 89 586 388 21 513 Total $ 487,942,073 $ 93,900,000 $ 435,919,191 $ 7,674,371 $ 295,610,894 $ 1,321,046,529 297,795 2003-04 Funding and FTE Data

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177 Gen.Rev. Lotter y Student WorkforceTotal FundsFTE COLLEGESCCPF CCPF FeesPBBFundingAvailableStudents Brevard $ 33 163 071 $ 3 897 478 $ 14 953 879 $ 347 714 $ 52 362 142 10 468 Broward 58 383 2426 861 47038 924 145618 863 104 787 720 22 959 Central Florida15 565 7841 829 3638 337 436121 783 25 854 366 4 763 Chi p ola 7 549 639887 2692 275 30956 462 10 768 679 1 651 Da y tona Beach41 238 0184 846 48414 273 280221 668 60 579 450 12 825 Edison 19 836 4992 331 27812 093 730199 444 34 460 951 7 121 Fla. JC @ Ja x 68 949 6398 103 28231 595 471445 784 109 094 176 19 939 Florida Ke y s4 887 336574 3831 377 56715 363 6 854 649 810 Gulf Coast15 100 6181 774 6956 972 963129 959 23 978 235 4 872 Hillsborou g h40 278 6754 733 73725 981 178400 864 71 394 454 16 816 Indian Rive r 37 759 9284 437 72211 803 509186 910 54 188 069 11 328 Lake Cit y 10 142 3981 191 9823 693 15640 320 15 067 856 2 509 Lake-Sumter7 284 561856 1153 781 23372 732 11 994 641 2 339 Manatee 17 479 2132 054 23811 752 072197 615 31 483 138 6 593 Miami-Dade134 287 41315 782 08283 500 027985 809 234 555 331 53 421 North Florida5 071 817596 0631 377 29331 245 7 076 418 1 001 OkaIoosa-14 417 4671 694 4086 641 551160 879 22 914 305 4 832 Palm Beach45 960 5405 401 49626 060 061465 271 77 887 368 15 875 Pasco13 581 9301 596 2126 674 790124 254 21 977 186 5 199 Pensacola30 908 0393 632 45710 798 458249 944 45 588 898 8 348 Polk 13 635 0051 602 4496 976 076146 098 22 359 628 4 506 Saint Johns 11 965 0231 406 1854 768 729103 282 18 243 219 3 786 Saint 47 708 4115 606 91429 067 992455 054 82 838 371 15 650 Santa Fe 29 813 5953 503 83218 957 272405 943 52 680 642 11 561 Seminole28 788 6993 383 38215 236 840194 441 47 603 362 11 243 South Florida12 048 2051 415 9612 378 96946 809 15 889 944 3 250 Tallahassee23 628 3502 776 91416 552 318391 680 43 349 262 10 257 Valencia 52 092 4716 122 14937 754 715858 181 96 827 516 20 896 Total $ 841,525,586 $ 98,900,000 $ 454,560,019 $ 7,674,371 $ $ 1,402,659,976 294,818 2004-05 Funding and FTE Data

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178 Gen.Rev. Lotter y Student WorkforceTotal FundsFTE COLLEGESCCPF CCPF FeesPBBFundingAvailableStudents Brevard $ 34 132 673 $ 3 911 249 $ 15 369 454 $ 813 103 $ 54 226 479 10 036 Broward 61 373 5477 032 45139 357 9111 497 849 109 261 758 22 220 Central Florida16 064 6301 840 7798 709 514289 943 26 904 866 4 578 Chi p ola 7 941 221909 1582 344 983128 553 11 323 915 1 662 Da y tona Beach42 250 0304 842 95614 512 562690 125 62 295 673 11 795 Edison 20 474 1872 347 52312 610 643445 205 35 877 558 7 091 Fla. JC @ Ja x 69 458 5247 963 02834 181 5341 243 115 112 846 201 19 619 Florida Ke y s5 094 051583 4631 365 93049 812 7 093 256 772 Gulf Coast15 540 8061 780 9527 130 906304 316 24 756 980 4 723 Hillsborou g h42 107 5794 826 34626 448 935918 353 74 301 213 16 395 Indian River38 712 9094 436 43113 079 796704 834 56 933 970 11 968 Lake Cit y 10 577 1851 212 7473 588 931173 712 15 552 575 2 381 Lake-Sumter7 786 123892 2613 909 131128 892 12 716 407 2 312 Manatee 18 160 3822 081 95812 317 877397 832 32 958 049 6 629 Miami-Dade141 217 13016 174 64083 359 6872 363 837 243 115 294 50 447 North Florida5 362 196614 6131 538 74364 622 7 580 174 1 010 OkaIoosa-15 038 0331 723 2917 208 689355 944 24 325 957 4 738 Palm Beach46 857 0215 370 11226 292 528966 046 79 485 707 15 406 Pasco14 321 2061 641 1077 180 357396 463 23 539 133 5 282 Pensacola31 409 8823 598 71510 683 306610 719 46 302 622 7 933 Polk 14 225 2851 630 4697 203 179309 051 23 367 984 4 636 Saint Johns 12 303 5471 410 0925 331 159227 373 19 272 171 3 687 Saint 49 719 5315 695 86931 866 311988 497 88 270 208 15 304 Santa Fe 30 891 2593 536 91619 625 524841 683 54 895 382 11 515 Seminole29 671 7523 401 33815 030 033706 866 48 809 989 10 646 South Florida12 389 8291 419 8602 322 728162 259 16 294 676 3 046 Tallahassee24 843 3782 838 31017 294 521625 795 45 602 004 11 013 Valencia 54 185 1306 208 36639 770 1071 671 197 101 834 800 20 872 Total $ 872,109,026 $ 99,925,000 $ 469,634,981 $ 18,075,996 $ $ 1,459,745,003 287,714 2005-06 Funding and FTE Data

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179 APPENDIX B. Raw data excerpt: population estim ates and projections by age, sex, race, and Hispanic origin for Florida a nd its counties, 2001-2006 and 2010. EstimateEstimateEstimateEstimateProjections County/RaceSex/Age20032004200520062010 ALACHUA All Races T otal231,296236,174240,764243,779259,838 0-411,88112,37613,14113,34414,381 5-1732,93532,92732,69532,93334,427 18-3488,31090,26093,13194,17599,893 35-5456,97458,03458,73458,73159,670 55-6418,93019,50120,49421,37225,238 65-7915,82416,40115,93816,42818,667 80+6,4426,6756,6316,7967,562 Female118,106120,704122,965124,480132,581 0-45,8246,0796,4576,5567,066 5-1716,07616,01115,89216,02616,823 18-3443,90144,98246,44046,97649,892 35-5429,60430,10330,50030,44330,704 55-649,78810,10110,58111,06613,192 65-798,7899,1288,8399,07110,147 80+4,1244,3004,2564,3424,757 Non-Hispanic Whit e T otal162,306163,828163,360164,068169,599 0-46,9517,3757,4777,5067,749 5-1719,64919,33818,67718,68018,998 18-3461,54261,66862,03862,11063,413 35-5441,28641,68941,37841,00240,169 55-6414,85915,24915,88516,41918,832 65-7912,64412,95712,42112,74914,273 80+5,3755,5525,4845,6026,165 Female 82,23983,16082,86883,21985,992 0-43,3923,6143,6733,6873,806 5-179,5299,3509,0219,0369,243 18-3430,23130,44530,67630,74531,526 35-5421,11121,28121,12920,89420,293 55-647,5687,7808,0748,3639,660 65-796,9777,1356,7996,9437,633 80+3,4313,5553,4963,5513,831 Non-Hispanic Blac k Total 45,59946,84149,55650,42154,697 0-43,4723,4163,9293,9924,307 5-179,0919,3039,5069,5559,909 18-3416,18116,82517,99018,38920,278 35-5410,91311,10111,66911,73812,205 55-642,9252,9903,2113,3864,135 65-792,2462,4012,4322,5202,916 80+ 771805819841947 Female 23,86824,55625,95326,40328,625 0-41,7091,6831,9321,9632,118 5-174,4594,5444,6424,6714,858 18-348,3938,7229,3049,48910,381Bureau of Economic and Business Research, University of Florida1 Population Estimates by Age, Sex, Race, and Hispanic Origin for Florida and Its Counties, 2003-2006, and Projections, 2010

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180 35-545,9236,0386,3566,3956,654 55-641,5961,6371,7571,8622,309 65-791,2821,3911,4101,4561,665 80+ 506541552567640 Hispanic Total 13,80715,59617,29918,47623,491 0-4 7288628989901,376 5-172,2852,3162,4872,6483,335 18-347,1848,2099,2739,73311,736 35-542,4822,8953,2033,4734,606 55-645306307148411,361 65-79464536569619835 80+ 134148155172242 Female 6,9877,7918,6199,19511,656 0-4 364426440485675 5-171,1501,1541,2401,3171,650 18-343,5143,9714,4794,7075,697 35-541,3271,5061,6621,7822,291 55-64289337376442715 65-79262308331360482 80+ 818991102146 BAKER All Races T otal23,38323,96323,95325,00426,904 0-41,6581,6531,7761,8301,879 5-174,4704,5584,5154,7125,069 18-345,7595,6845,6705,8756,164 35-546,9617,2697,1967,4187,631 55-642,2692,3892,4332,6123,080 65-791,7971,9161,8802,0262,403 80+ 469494483531678 Female11,01111,18111,10811,61712,582 0-4 824817873899923 5-172,1582,2032,1602,2562,437 18-342,5152,4162,3762,4622,573 35-543,1583,2483,2113,3253,473 55-641,1101,1771,2011,2901,526 65-799269909691,0431,239 80+ 320330318342411 Non-Hispanic Whit e T otal19,37419,99619,90120,84122,431 0-41,3991,3811,4921,5351,549 5-173,7163,8853,8113,9974,322 18-344,5184,3964,3244,4784,628 35-545,6845,9995,9476,1586,368 55-642,0182,1392,1702,3352,746 65-791,6291,7521,7211,8592,210 80+ 410444436479608 Female9,4619,7349,66810,14010,977 0-4 695683733754761 5-171,7831,8651,8351,9292,104 18-342,1552,0712,0322,1012,159 35-542,7182,8532,8182,9283,066 55-649941,0621,0801,1651,379 65-798369048859561,140 80+ 280296285307368 Non-Hispanic Blac k T otal3,3313,2373,2973,3223,372 0-4 212230244249262 5-17636557575570552 18-341,0071,0311,0791,0991,168 35-541,0651,0311,005995941 55-64217211222229253 65-79144135132137149 80+5042404347 Female1,3451,2341,2351,2441,254 0-4 105114120122129 5-17321283273269251 18-34309292294301324Bureau of Economic and Business Research, University of Florida2

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181 Hispanic T otal 5465306397051,072 0-4 4037434561 5-17 11099120125162 18-34 168163199232390 35-54 168168200218326 55-64 2626354280 65-79 2728313135 80+ 7 9111218 Female194182221233320 0-4 2018212230 5-17 5045555777 18-34 5044535882 35-54 5152656786 55-64 7 6 81021 65-79 1313151414 80+ 3 4 4 510 FLORID A All Races T otal17,071,50817,516,73217,918,22718,349,13219,974,199 0-41,019,3281,040,8941,070,2051,092,9951,179,974 5-172,838,1442,898,0062,972,2273,020,7703,199,828 18-343,606,4083,690,6003,777,4343,869,4394,227,240 35-544,838,7084,944,7055,062,7575,137,0095,414,041 55-641,836,6131,890,9591,979,7582,081,4132,471,845 65-792,072,5752,156,7932,140,3272,196,4912,396,125 80+859,732894,775915,519951,0151,085,146 Female8,720,2408,954,3519,152,9359,370,03410,190,548 0-4498,509510,520525,634536,771579,484 5-171,387,2361,412,9881,449,7811,474,2341,565,066 18-341,769,1581,809,7141,851,8581,896,1042,068,958 35-542,451,3912,500,9912,558,9052,594,1652,725,680 55-64969,089996,6951,042,4131,094,6041,294,908 65-791,124,5791,177,8421,168,1591,198,3651,306,379 80+520,278545,601556,185575,791650,073 Non-Hispanic White T otal11,120,30411,196,12811,277,64611,427,91711,893,250 0-4548,000536,266534,919539,122549,474 5-171,577,4541,586,3101,599,2721,599,7471,582,638 18-341,997,8962,007,5722,014,5102,042,9232,136,608 35-543,194,5733,176,4173,197,0443,193,2983,145,453 55-641,389,3221,403,4661,460,4661,521,1081,743,887 65-791,673,9101,720,9911,691,1451,725,2951,833,413 80+739,149765,106780,290806,424901,777 Female5,692,7045,734,4185,772,2945,848,1876,082,430 0-4267,517262,774262,755264,812269,900 5-17768,426771,128777,620778,543772,982 18-34983,302986,007989,2711,002,5281,045,885 35-541,602,3561,590,3221,599,6631,597,3221,571,287 55-64727,894732,934761,499791,685901,880 65-79900,639930,242913,183931,064987,630Bureau of Economic and Business Research, University of Florida93

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182 80+442,570461,011468,303482,233532,866 Non-Hispanic Black T otal2,552,2822,659,1542,776,6022,851,2513,158,870 0-4214,713223,924234,497239,275259,115 5-17587,680601,909622,974631,116665,340 18-34682,198706,634738,889758,922842,815 35-54698,589731,217764,692780,542846,954 55-64183,693197,116210,875226,619289,755 65-79143,898155,237160,026167,627197,814 80+41,51143,11744,64947,15057,077 Female 1,323,7431,381,4591,442,0401,480,4271,639,168 0-4105,396110,171115,351117,685127,443 5-17290,122296,142306,352310,316327,147 18-34348,354360,359376,271385,051422,176 35-54371,231388,939407,002415,608451,706 55-6499,691107,690115,374124,201159,628 65-7981,68889,30691,88396,144113,173 80+27,26128,85229,80731,42237,895 Hispanic T otal3,006,7713,247,1883,425,4173,613,4824,393,095 0-4223,628245,986264,029276,545328,123 5-17582,893615,876651,198688,557840,253 18-34822,643867,259908,433947,2901,108,327 35-54837,367922,411979,4801,037,3681,278,565 55-64234,966259,387274,830297,092389,353 65-79232,492256,341263,827276,666331,675 80+72,78279,92883,62089,964116,799 Female1,500,0361,622,7541,710,2581,803,7742,193,643 0-4109,408120,499129,444135,556160,861 5-17284,229299,527317,246335,538410,048 18-34384,440407,456427,156447,173530,573 35-54420,071460,492487,303513,999626,139 55-64125,921139,100147,110158,611206,436 65-79129,627144,364148,557155,727186,554 80+46,34051,31653,44257,17073,032Bureau of Economic and Business Research, University of Florida94

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183 LIST OF REFERENCES Albright, B. N. (1996). From business as usual to funding for results [On-line]. Ohio Board of Regents: Higher Educa tion Funding Commission. Retr ieved November 19, 2006 from http://www.regents.state. oh.us/hefc/albright96.html Baldwin, J. (2000). Liberal arts for a new millenn ium. Carnegie Corporation of New York, 1(1). Retrieved November 19, 2006 from Carnegie Reporter Web site: http://www.carnegie.org/reporte r/01/liberal_arts/index.htm l Berne, R. & Stiefel, L. (1979). Concepts of equ ity and their relationship to state school finance plans. Journal of Education Finance, 5, 109-132. Berne, R. & Stiefel, L. (1984). The measuremen t of equity in school finance: Conceptual, methodological, and empirical dimensions. Baltimore: Johns Hopkins University. Bezeau, L. M. (1979). Measures of inequality of per pupil expenditures: Application to Ontario. Journal of Education Finance, 5, p. 33-148. Boone, E.J. (1997). National Perspective of Community Colleges. Community College Journal. 21(1) 1-12. Brown, R. (1999). A study of equity in a multi-in stitution community college system prior to and after implementing performance-based fundi ng (Doctoral dissertati on, University of Florida, 1999). Dissertation Abstracts International. 6009A,3248. Burke, J. C. (2002). Performance Reporting: Th e Preferred No Cost Accountability Program, Sixth Annual Survey 2002. Retrieved Novemb er 26, 2006, from Rockefeller Institute of Government Web site: http://www.rockin st.org/WorkArea/show content.aspx?id=8454 Burke, J. C. (2003a). Accountability Reporting, With So Much Effort; Why So Little Results, The Nelson A. Rockefeller Institute of G overnment. Retrieved November 26, 2006, from SHEEO Web site: http://64.233.179.104/schol ar? h l=en&lr=&q=cache:jHQIDQUw04J:www.sheeo.org/acco unt/comm/testim/Bur ke%2520testimony.pdf+ Burke, J. C. (2003b). Performance Reporting: R eal Accountability or Accountability Lite Seventh Annual Survey 2003, The Nelson A. Rockefeller Institute of Government. Retrieved November 23, 2006, fr om K20 Accountability Web site: http://64.233.179.104/scholar?h l=en&lr=&q=cache:7BVsfhj7zcJ:www.k20accountabil ity.org/docs/OtherRes_Roc kReportPerform Rprtg.pdf+ Burke, J. C. & Serban, A M. (1997a). Stat e performance funding a nd budgeting for public higher education: current status and future prospects. In J. C. Burke & A. M. Serban, Performance funding and budgeting for public higher education: current status and future prospects. Albany, NY: Nelson A. Rockefeller Institute of Government.

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191 BIOGRAPHICAL SKETCH Conferlete Carney was born on March 10, 1948 in Tarboro, North Carolina. The youngest of three children, he grew up in Tarboro, graduating from W. A. Pattillo High School in 1966. He earned his A.S in Electronics Technologies and B.S. in Industrial Technologies from North Carolina Agricultural and Technical Univ ersity (A&T) in 1968 and 1969, respectively. He earned his Masters of Business Administration from North Carolina Central University in Durham, North Carolina in 1981. Upon graduating in 1969 with his A.S and B.S degrees, he joined GTE Corporation as an associate engineer in central office switching systems. He remained with GTE for 27 years, progressing to increasing levels of responsibil ity in engineering, e ngineering management, advanced network planning, in ternational telecomm unications standards, and technology planning. Having resided in North Carolina, Ariz ona, Connecticut, and Florida, he retired from his first career with GTE Corporation in May 1996. In November 1996, he joined St. Petersburg Juni or College as Director of Administrative Information Systems. He was promoted to Vice President of Information Systems in 1998, and the assumed the combined responsibilities for information systems, business services, budgeting and planning in 2001. His position at St. Petersbu rg Junior College (now St. Petersburg College) afforded him opportunities to learn and work in in stitutional effectivenes s, financial assistance services, strategic planning, budget planning, technology planning, and the Florida Community Colleges Funding Formula Committee. He began his pursuit of the Ph.D. in Higher Education Leadership in September 2001. Upon completion, Conferlete wishes to continue his career in highe r education leadership. He is married to Angela Picard Carney, who also will also earn her Ph.D. in 2007.