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Perceptions of Traits of Women in Construction

Permanent Link: http://ufdc.ufl.edu/UFE0024445/00001

Material Information

Title: Perceptions of Traits of Women in Construction
Physical Description: 1 online resource (135 p.)
Language: english
Creator: Wangle, Amber
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: construction, gender, perceptions, personality, recruitment, traits, women
Building Construction -- Dissertations, Academic -- UF
Genre: Building Construction thesis, M.S.B.C.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Studies have shown that men and women perform differently on tasks. This difference can be attributed to a degree to their sex. Studies have also shown that women are predominately employed in ?lighter? construction trades and are not employed in significant numbers in trades consisting of more laborious tasks. What has not been studied is the relationship between the unique gender skill sets and the placement of women in construction firms. There is also a lack of information on whether construction firms are actively recruiting women. When the labor shortages of the past return, the industry should be actively looking to change its offensive identity and reach out to untapped labor sources. The objective of this study was to determine and analyze the perceived trends of women in construction with regards to recruitment practices and placement within firms on the basis of gender. Data and literature on construction industry recruitment strategies, differences in gender, and representation of women in the trades has been studied in order to understand the perceived status of women in the construction industry as a whole. The research used surveys to collect data from the construction industry. The construction companies targeted for this research included all types of contractors and subcontractors, from a pool of attendees of the M.E. Rinker School Career Fair. This ensured that only companies that were actively recruiting and have some type of company recruitment program in place completed a survey. The data collected were analyzed and statistically significant relationships were noted. Recommendations were then developed according to the results of the data analysis. Major findings of the study included correlations between the size and type of construction firms and the proportions of women employed. The analysis determined that there are greater opportunities for women in home office positions in smaller firms. It was also determined that the greater the amount of work that is subcontracted, the greater the proportion of women home office personnel and salaried employees. Other findings from the study included patterns of how the industry ranked women?s performance of tasks. Construction industry professionals rated women higher in tasks involving computer literacy skills than did student respondents. Both industry professionals and student respondents thought women perform slightly better at tasks involving communication skills and sensitivity to the emotions of others, and that women performed worse than men in tasks involving physical strength. In regards to observations of personality traits, industry professionals and student respondents thought that women were slightly more tenderminded and organized as compared to men, while men were slightly more aggressive than women. The results helped to concluded that while companies are not necessarily discriminating against women, they are also not looking to them as a potential skilled labor source. Additionally, gender differences observed in construction work, are not reflected when assigning work. In times when gender is considered, physical strength is typically the only gender difference that the industry is recognizing.
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.
Statement of Responsibility: by Amber Wangle.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2009.
Local: Adviser: Hinze, Jimmie W.
Local: Co-adviser: Issa, R. Raymond.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024445:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024445/00001

Material Information

Title: Perceptions of Traits of Women in Construction
Physical Description: 1 online resource (135 p.)
Language: english
Creator: Wangle, Amber
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: construction, gender, perceptions, personality, recruitment, traits, women
Building Construction -- Dissertations, Academic -- UF
Genre: Building Construction thesis, M.S.B.C.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Studies have shown that men and women perform differently on tasks. This difference can be attributed to a degree to their sex. Studies have also shown that women are predominately employed in ?lighter? construction trades and are not employed in significant numbers in trades consisting of more laborious tasks. What has not been studied is the relationship between the unique gender skill sets and the placement of women in construction firms. There is also a lack of information on whether construction firms are actively recruiting women. When the labor shortages of the past return, the industry should be actively looking to change its offensive identity and reach out to untapped labor sources. The objective of this study was to determine and analyze the perceived trends of women in construction with regards to recruitment practices and placement within firms on the basis of gender. Data and literature on construction industry recruitment strategies, differences in gender, and representation of women in the trades has been studied in order to understand the perceived status of women in the construction industry as a whole. The research used surveys to collect data from the construction industry. The construction companies targeted for this research included all types of contractors and subcontractors, from a pool of attendees of the M.E. Rinker School Career Fair. This ensured that only companies that were actively recruiting and have some type of company recruitment program in place completed a survey. The data collected were analyzed and statistically significant relationships were noted. Recommendations were then developed according to the results of the data analysis. Major findings of the study included correlations between the size and type of construction firms and the proportions of women employed. The analysis determined that there are greater opportunities for women in home office positions in smaller firms. It was also determined that the greater the amount of work that is subcontracted, the greater the proportion of women home office personnel and salaried employees. Other findings from the study included patterns of how the industry ranked women?s performance of tasks. Construction industry professionals rated women higher in tasks involving computer literacy skills than did student respondents. Both industry professionals and student respondents thought women perform slightly better at tasks involving communication skills and sensitivity to the emotions of others, and that women performed worse than men in tasks involving physical strength. In regards to observations of personality traits, industry professionals and student respondents thought that women were slightly more tenderminded and organized as compared to men, while men were slightly more aggressive than women. The results helped to concluded that while companies are not necessarily discriminating against women, they are also not looking to them as a potential skilled labor source. Additionally, gender differences observed in construction work, are not reflected when assigning work. In times when gender is considered, physical strength is typically the only gender difference that the industry is recognizing.
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.
Statement of Responsibility: by Amber Wangle.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2009.
Local: Adviser: Hinze, Jimmie W.
Local: Co-adviser: Issa, R. Raymond.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024445:00001


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1 PERCEPTIONS OF TRAITS OF WOMEN IN CONSTRUCTION By AMBER M. WANGLE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2009

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2 2009 Amber M. Wangle

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3 To my loving and supporting family

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4 ACKNOWLEDGMENTS I would like to thank my pare nts and all of my family, for their love, support, and encouragement. I would also like to extend my l ove and thanks to my fianc, Kevin, whose love has been a great motivator. I would also like to extend a special thanks to Dr. Jimmie Hinze for giving me the opportunity to work with him on my resear ch. His exceptional knowledge has helped me throughout this learning process. I would also lik e to thank the rest of my committee, Dr. R. Raymond Issa and Dr. E. Douglas Lucas.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ............................................................................................................... 4LIST OF TABLES ................................................................................................................ ...........7LIST OF FIGURES ............................................................................................................... ..........8ABSTRACT ...................................................................................................................... .............11 CHAPTER 1 INTRODUCTION ................................................................................................................ ..13Introduction .................................................................................................................. ...........13Objective of the Study ........................................................................................................ ....13Hypothesis Statement .......................................................................................................... ...14Overview ...................................................................................................................... ...........142 LITERATURE REVIEW .......................................................................................................17Background: Recruiting Women into the Trades ...................................................................17Advantages for Women ...................................................................................................17Advantages for the Industry ............................................................................................19Barriers to Entry ............................................................................................................. .19Current Recruitment Strategies .......................................................................................22Conclusions ................................................................................................................... ..26Unique Skill Sets by Gender ................................................................................................... 27Introduction .................................................................................................................. ...27Physical Abilities ............................................................................................................ .28Musculoskeletal differences .....................................................................................28Personal protection equipment and body types ........................................................30Manual dexterity ......................................................................................................31Spatial abilities .........................................................................................................32Leadership/Management Abilities ...................................................................................33Emotional intelligence – recognizing emotions .......................................................33Communication and verbal abilities .........................................................................34Supervision ...............................................................................................................34Group behavior .........................................................................................................34Leadership ................................................................................................................36Technological/Mathematical Abilities ............................................................................37Computer literacy .....................................................................................................37Mathematical abilities ..............................................................................................38Conclusions ................................................................................................................... ..40Personality Traits by Gender .................................................................................................. 41Background .................................................................................................................... ..41

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6 Proximal Causes ..............................................................................................................4 1Biological model ......................................................................................................41Socio-cultural model ................................................................................................42Distal Causes ................................................................................................................. ..43Conclusions ................................................................................................................... ..43Women in the Construction Trades ........................................................................................44Job Satisfaction .............................................................................................................. ..44Representation ................................................................................................................ .45Comparison to similar occupations ..........................................................................47Women in the Rinker School ...................................................................................503 METHODOLOGY ................................................................................................................. 53Introduction .................................................................................................................. ...........53Survey Questionnaires Designed ............................................................................................53Sample Selection .............................................................................................................. ......54Surveys Conducted ............................................................................................................. ....55Data Analysis ................................................................................................................. .........564 RESULTS ..................................................................................................................... ..........57Survey Response Rate .......................................................................................................... ..57Respondent Demographics .....................................................................................................57Employee Pl acement ............................................................................................................ ..66Employee Recr uitment .......................................................................................................... .71Skill Productivity Observations ..............................................................................................7 3Personality Trait Observations ...............................................................................................9 2Women in the Trades ........................................................................................................... .1055 CONCLUSIONS ................................................................................................................. .107 APPENDIX A INSTITUTIONAL REVIEW BO ARD SURVEY APPROVAL .........................................116B SURVEY COVER LETTER ................................................................................................119C SURVEY ...................................................................................................................... ........120D STATISTICAL CORRELATION TABLES ........................................................................124E RESPONSE TABLES ..........................................................................................................128LIST OF REFERENCES ............................................................................................................ .132BIOGRAPHICAL SKETCH .......................................................................................................135

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7 LIST OF TABLES Table page 2-1 Employed persons by detailed occupation and gender, 2006 annual averages (Numbers in thousands) .....................................................................................................485-1 Advantages by gender in skills and tasks used in construction .......................................1105-2 Tendencies by gender of personality traits. .....................................................................112D-1 Respondent demographi cs correlation tests .....................................................................124D-2 Correlation coefficients of skills/tasks .............................................................................125D-3 Correlation coefficients of personality traits ....................................................................126D-4 Correlation coefficients of skills /tasks and personality traits. .........................................127E-1 Interaction in peer groups ................................................................................................ 128E-2 Differences in productivity ..............................................................................................1 30E-3 Women in the trades ....................................................................................................... .131

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8 LIST OF FIGURES Figure page 2-1 Percentage of women empl oyed in construction trades .....................................................462-2 Comparison of representation of women in construction and extraction occupations versus women in architecture and engineering occupations ..............................................494-1 Types of projects performed by respondents. ....................................................................584-2 Types of employers of respondents. ..................................................................................584-3 Percent of work subcontracted. ..........................................................................................594-4 Construction industry position of respondents. .................................................................604-5 Students’ amount of c onstruction experience. ...................................................................614-6 Gender composition of industry professi onal and student surv ey respondents. ................614-7 Gender composition of industr y professional respondents. ...............................................624-8 Gender composition of student respondents. .....................................................................624-9 Numbers of field employees. .............................................................................................634-10 Numbers of home office personnel. ...................................................................................644-11 Proportion of wome n field employees. ..............................................................................654-12 Proportion of women home of fice and salaried employees. ..............................................654-13 Office positions of women. ............................................................................................... .674-14 Field positions of women. ................................................................................................ ..674-15 Proportions of women in trad es on companies’ projects. ..................................................694-16 Gender is a consideration when assigning work to new hires. ..........................................704-17 Company has policies against hiring women. ....................................................................714-18 Company has a program to target women for employment. ..............................................724-19 Observations from industry profession als and student respondents on skill/task performance. .................................................................................................................. ....744-20 Observations from industry professional respondents on skill/task performance. ............75

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9 4-21 Observations from men industry professi onal respondents on skill/t ask performance. ....754-22 Observations from women industr y professional respondents on skill/task performance. .................................................................................................................. ....774-23 Observations from student res pondents on skill/task performance. ..................................774-24 Observations from men student re spondents on skill/task performance. ..........................784-25 Observations from women student re spondents on skill/task performance. ......................794-26 Observations from respondents with c onstruction work experience on skill/task performance. .................................................................................................................. ....804-27 Observations from respondents with no construction work ex perience on skill/task performance. .................................................................................................................. ....804-28 Manual dexterity, average rankings by group. ...................................................................824-29 Physical strength, average rankings by group. ...................................................................824-30 Spatial perception, av erage rankings by group. .................................................................834-31 Leadership skills, av erage rankings by group. ...................................................................834-32 Group interaction/teamwork, average rankings by group. .................................................844-33 Supervision of other worker s, average rankings by group. ...............................................844-34 Communication, average rankings by group. ....................................................................854-35 Sensitivity to the emotions of others, average rankings by group. ....................................854-36 Computer literacy, av erage rankings by group. .................................................................864-37 Mathematical calculatio ns, average rankings by group. ....................................................864-38 Female employees express more con cern about musculoskeletal injuries. .......................884-39 Company supplies PPE especially for women...................................................................894-40 Assertiveness, av erage rankings by group. ........................................................................934-41 High self-esteem, average rankings by group. ...................................................................944-42 Extroversion, average rankings by group. .........................................................................954-43 Anxiety, average rankings by group. .................................................................................96

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10 4-44 Creative/idea generating, average rankings by group. .......................................................964-45 Stress, average rankings by group. ....................................................................................974-46 Trust, average rankings by group.......................................................................................984-47 Aggression, average rankings by group. ............................................................................994-48 Tender-mindedness, average rankings by group. ..............................................................994-49 Impulsive, average rankings by group. ............................................................................1004-50 Hard-working, average rankings by group. .....................................................................1014-51 Organization, average rankings by group. .......................................................................1024-52 Self-control, averag e rankings by group. .........................................................................1024-53 Dedication, average rankings by group. ..........................................................................1034-54 Industry professionals’ a nd students’ average rankings of personality traits. .................1044-52 Suitability in trades. ................................................................................................... ......1065-1 Findings of observations from industry professionals and student respondents on skill/task performance. .....................................................................................................11 15-2 Findings of industry professionals’ and st udents’ average rankings of personality traits......................................................................................................................... .........113

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11 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Bu ilding Construction PERCEPTIONS OF TRAITS OF WOMEN IN CONSTRUCTION By Amber M. Wangle May 2009 Chair: Jimmie Hinze Cochair: R. Raymond Issa Major: Building Construction Studies have shown that men and women perf orm differently on tasks. This difference can be attributed to a degree to their sex. Studies have also s hown that women are predominately employed in ‘lighter’ construction trades and are not employed in significant numbers in trades consisting of more laborious tasks. What has not been studied is the relationship between the unique gender skill sets and the pl acement of women in construction firms. There is also a lack of information on whether construction firms ar e actively recruiting women. When the labor shortages of the past return, the industry should be actively lo oking to change its offensive identity and reach out to untapped labor sources. The objective of this study wa s to determine and analyze th e perceived trends of women in construction with regards to recruitment prac tices and placement within firms on the basis of gender. Data and literature on construction industr y recruitment strategies, differences in gender, and representation of women in the trades has b een studied in order to understand the perceived status of women in the constr uction industry as a whole. The research used surveys to collect data from the construction industry. The construction companies targeted for this res earch included all types of contractors and subcontractors, from a pool of attendees of th e M.E. Rinker School Career Fair. This ensured

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12 that only companies that were actively recruiti ng and have some type of company recruitment program in place completed a survey. The data collected were analy zed and statistically significant relationships were not ed. Recommendations were then developed according to the results of the data analysis. Major findings of the study in cluded correlations between the size and type of construction firms and the proportions of wome n employed. The analysis determ ined that there are greater opportunities for women in home office positions in sm aller firms. It was also determined that the greater the amount of work that is subcontra cted, the greater the pr oportion of women home office personnel and salaried employees. Other findings from the study in cluded patterns of how the industry ranked women’s performance of task s. Construction industr y professionals rated women higher in tasks involving co mputer literacy skills than di d student respondents. Both industry professionals and student respondents thought women perfor m slightly better at tasks involving communication skills and sensitivity to the emotions of others, and that women performed worse than men in tasks involving physic al strength. In regards to observations of personality traits, industry pr ofessionals and student respond ents thought that women were slightly more tenderminded and organized as co mpared to men, while men were slightly more aggressive than women. The results helped to concl uded that while companies are not necessarily discriminating against women, they are also not looking to them as a potential skilled labor source. Additionally, gender differences observed in cons truction work, are not re flected when assigning work. In times when gender is considered, physical strength is t ypically the only gender difference that the indus try is recognizing.

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13 CHAPTER 1 INTRODUCTION Introduction Previous studies are inconclusive as to whether the construction industry has yet to actively seek out ways to successfully recrui t women (Moccio 2006). This confusion may be attributed to the lack of training and hiring programs for women on the industries part, or the neglect for creating an atmosphere where new female recruits are regarded with respect amid the male veterans of the industry, since previous opposition to female worker s has been well noted. Studies have shown that me n and women perform differently on tasks. This difference can be attributed to a degree to their sex. Studies have also s hown that women are predominately employed in ‘lighter’ construction trades and are not significantly present in trades consisting of more laborious tasks. What has not been stud ied is the relationship between the unique gender skill sets and the placement of women in construc tion firms. With current labor shortages that are only expected to get worse, the industry shou ld be actively looking to change its offensive identity and reach out to untapped labor sources. Objective of the Study The objective of this study wa s to determine and analyze th e perceived trends of women in construction with regards to recruitment prac tices and placement within the firm on the basis of gender. Data and literature on construction industry recruitm ent strategies, differences in gender, and representation of wo men in the trades has been st udied in order to understand the perceived status of women in the co nstruction industry as a whole. The research method involved su rveys to collect data from the construction industry. The construction companies targeted for this res earch included all types of contractors and subcontractors, from a pool of attendees of th e M.E. Rinker, Sr. School of Building Construction

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14 Career Fair. This ensured that only companies that were activel y recruiting and have some type of company recruitment program in place comple ted a survey. Utilizing statistical analysis, observations were concluded and recommendations were then given according to the results. Hypothesis Statement The hypotheses tested were as follows: H0: A relationship exists between the gender of an employee and their placement or position within the company. H0: Construction companies are not specif ically targeting women for recruitment into the industry. H0: Employers perceive men and women to have specific gender a ssociated skills and personality traits. These perceptions follow gender stereotypes rather than proven gender differences. Overview Chapter 2 presents a literature review on recent implemented construction industry recruitment strategies toward women, differences in gender skills and traits with consideration to gender stereotypes, and data analysis of the re presentation of women in the trades, women in similar schools within th e University of Florida and women in the M.E. Rinker, Sr. School of Building Construction. The review also includes a background to women in construction; the advantages for women to enter the construc tion industry, both for th emselves and for the companies in which they will work; and hindr ances for women entering the industry including preconceptions, internal barri ers, and external barriers. Chapter 3 provides the methodology used to conduct this resear ch. There was no specifically targeted group or t ype of contractor. A total of 108 surveys were conducted. The research plan consisted of two surveys; a studen t survey, distributed manually, and a survey for

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15 industry professionals, distribut ed electronically. The basis of selection for the industry professional survey was that the company had a ttended an M.E. Rinker, Sr. School of Building Construction Career Fair. The contact informati on was gathered from the Career Fair materials so that only companies that were actively recr uiting and have some type of company recruitment program in place completed surveys. The student survey was completed by graduate students of the Rinker School. The survey was designed to obtain qualitative and quantitative information needed on trends of women in construction. The beginning of the survey was designed to collect demographic information about the respondent’s construction company. The second objective of the survey was to discover if the company had an y specialized recruitment program or effort in place for the hiring of women or any particular re cruitment practice against the hiring of women. This part of the survey questionnaire was both a quantitative trend and a qualitative descriptive answer portion. The third part of the survey was to determine the number of women employed in that company and the placement or position of those women within the construction firm. The fourth part of the survey obtains observations of women’s task performance. Similarly, the fifth part of the survey deals with observations of personality traits. The final portion of the questionnaire deals with the observations of women in the co nstruction trades. Chapter 4 provides a discussion of the analys is performed on the results of the survey. The findings of the research are based on a total of 108 completed surveys that were received. A total of 261 surveys were dispersed, representi ng a response rate of 41.4%. In the student survey, 62 surveys were manually distributed and 62 surveys were received, representing a response rate of 100%. In the industry professi onal survey, 212 surveys were electronically distributed to personnel in management positions. Of those, 13 were returned as undeliverable, leaving a total of 199 industry pr ofessional surveys dist ributed. There were 46 responses to the

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16 industry professional survey, representing a re sponse rate of 23.1%. A discussion of the statistical analysis used to study th e data collected is introduced. Chapter 5 is the final chapter of this thesis and provides a conclusion of the research and results by summing up the study performed in this work. Each hypothesis is accepted or rejected based on the results of the statis tical analysis. Finally, recomme ndations for future research on gender in the construction industry are made.

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17 CHAPTER 2 LITERATURE REVIEW Background: Recruiting Women into the Trades Studies are inconclusive as to whether the construction industry has yet to actively seek out ways to successfully recruit women (Moccio 2006). This confus ion may be attributed to the lack of training and hiring programs for women on the industries part, or the neglect for creating an atmosphere where new female recruits are rega rded with respect amid the male veterans of the industry, since previous oppos ition to female workers has b een well noted. However, with current labor shortages that are only expected to get worse, the industry should be actively looking to change its offensive id entity and reach out to untapped labor sources. Hence, how can the construction industry attract new female recruits with this alre ady tainted image? To answer this, the industry needs to look more closely at what advantages there ar e for women to enter the construction industry, both for themselves and for the companies in which they will work; what hindrances there are for women en tering the industry in cluding preconceptions, internal barriers, and external barriers, and lastly; what strategies are successful in recruiting and retaining women employees in the c onstruction industry. Advantages for Women To some extent, all people are driven by money. Skilled blue-collar work usually involves high pay. Typical wages for the first year of apprenticeship range from $10 $17 an hour. After the completed apprenticeship, wages ma y increase to as much as $45 an hour (NEW 2007). These rates are much higher than most entry-level wages. There is also a great opportunity and likelihood of promotion, and the start of a car eer path. Construction is one of the few businesses where you can work your way from the bottom up. Prospects to own your own business are greater in construction than an y other trade. A study in 2007 proclaimed that

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18 women-owned construction companies comprise more than 12% of the market (Fisher 2007). With the average household income around merely $36,000 a year, a career in construction looks very attractive. Numerous women have conc luded that an occupation in construction will provide them better opportunitie s (Nesby 1999). The higher wage rates of construction are especially attractive to women w ith children. The higher wage rates would enable them to afford childcare. Women with children show a greater willingness to transfer to nontraditional occupations, such as construction, than women w ithout children (Moccio 2006) This is because women with children are more likely to have eco nomic need as their main motivating factor. Studies also show that for African-American women, the main motivating factor is economic need. Women of color may also be more inclined to consider blue collar work because of prior exposure to customarily male tasks during upbringi ng. Entry into higher paying blue collar work permits women of color the chance to progress in the labor market, in te rms of both status and earnings. Because women of color are the most open to this nature of work, they should be specifically targeted by recruitment efforts fo r the construction busine ss (Moccio 2006). Along with the advantages of higher wages, jobs in construction usually have excellent medical benefits, pensions, and paid annuities, an d provide both technica l classroom training and on-the-job training (NEW 2007). A study in New York in 2006 showed that “at least 50% of construction jobs are living wage jobs with union ized benefits that coul d significantly increase the living standard of welfare to work mothers” (M occio 2006). With all of the benefits to blue collar type work in constructi on, one would think that it would be a difficult industry to break into. However, the greatest advantage to the co nstruction industry is just the opposite. The jobs do not entail extreme training or natural inborn talent. It is quite easy for anyone having the

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19 physical ability to start at the bottom and wo rk their way up the ladder. There are also advantages for the companies th at will hire these women. Advantages for the Industry More and more construction companies are b ecoming conscious of the fact that diversity practices add economic worth for thei r clientele. Variations in id eas, talent, and skills enhance their competitive advantage in an insistent mark et. Developing the cultural aptitudes of all people will add to their worth in society and the companies a nd organizations in which they work. Companies that have previously co me to this understanding are founding mentoring programs for minority and women contractors and hiring consulti ng firms to support them in achieving these new cultural competencies (Nes by 1999). With advantages both for women and for the companies in which they will be em ployed, the following question arises: Why aren’t there more women in the construction industry? Barriers to Entry Women may be shying away from working in the construction industry because of preconceptions about the work. Customarily, women’ s lack of interest in male blue collar work, such as construction, has been attributed to either socially devel oped partialities for sexappropriate occupations and/or the result of men’s treatmen t of women who do enter these nontraditional professions (Moccio 2006). More r ecent studies indicate that there may be other reasons which explain why women do not typically pursue jobs in construction or other male dominated occupations. The resu lts of the research state that women may prefer white-collar employment to blue collar empl oyment because of the inherent characteristics of each type of employment. Women may also se ek out only ‘socially acceptable’ employment. They may stay away from jobs that they think may result in negative feedback and harassment from family members, friends, male co-workers, and employe rs. Women may be acting on culturally formed

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20 beliefs embedded from adolescence that construction is a “man’s job”. Additionally, some women may have formerly been subjected to se x discrimination in hiri ng and employment or suffered from harassment on the job. These women may no longer wish to work in blue collar employment. Industry analysts reas on that years of discriminati on and sexual harassment in the field is revolting prospective female candidates for the industry. Many contractors may also be under the influence that women are physically incapab le to execute the tasks of the post and may be disinclined to hire them based on that err oneous idea. Along these same lines, women may believe that they are unqualified for blue coll ar work. They may be uninformed of job requirements and of job training programs and a pprenticeships. A final reason may be due to labor conditions: trades people are exposed to extreme weather; the work is cyclical; apprenticeship wages are low; and the risk of onthe-job injury is great. The hours and work schedules of a number of blue collar jobs may thwart women, particularly women with young children, from seeking blue collar employment. “Blatant sexual harassment and the constant questioning of their abilities a nd qualifications, as reported by current women construction laborers, have created a tainted image and re putation of the construc tion industry” (Moccio 2006). Sexual harassment is not only a preconcep tion or a problem with the image of the construction industry; it is also a very real hindrance for women in construction professions. The executive director of the National Organiza tion for Women’s Legal Defense and Education Fund, Helen R. Neuborne, agrees, and adds that ev en when women manage to attain an opening in an apprenticeship programs, their on-the-j ob treatment often becomes an impediment to natural job progression. “They’re sent for coffee, they’re put off by themselves, they’re sexually harassed, men urinate next to them,” she said. “The re is so very little incentive to stay” (Bishop

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21 1991). Another testimony to this awful treatment is from Linda Jofuku, a former carpenter who is now the business representative for the Intern ational Federation of Pr ofessional and Technical Engineers. She testified that she was doused wi th water while working with electrical wires and grabbed and fondled while carrying heavy loads up la dders. “You get really sick of it,” she said (Bishop 1991). Women may also face problems or obstacles from the company at large in hiring practices. Many constructi on companies have hesitated in establishing women contractor development programs because these programs are often viewed as unfair practices or reverse discrimination. This has also been a problem for minority work ers. Construction companies also may not see this part of the company’s de velopment as a high priori ty. A 1999 article about diversity in construction companies said that this may be partially attributed to profit margins. “Because profit margins are so thin, many construc tion companies are in survival mode, forced to reduce their workforce, subcont ractors and supplier base. Othe r contractors’ work load has increased so much it forces them to be in re actionary mode, relying on traditional methods for recruiting and hiring personnel” (Nesby 1999). Additionally, women may be hindered from entering into construction work because of lack of math skills, tool familiarity, and physical conditioning. This stems from the traditional belief that construction is “men’s work”. Because of this belief, women may have been pushed away fr om these subjects in school or told that they couldn’t do them or wouldn’t be good at them. To confront these negative viewpoints, there is a need for active strategies in outreach and career e xploration. The hope is that these strategies can counteract the ingrained gende r tendencies and allow women to be comfortable in choosing to train for a non-traditional o ccupation (Moccio 2006). Also, wo men have historically lacked access to the “old-boys network”, which are so clos ely tied to the construction industry. Without the access, women are barred from the informal networks through which most positions are

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22 filled. The greatest obstacle of recruitment strate gies is to make sure that qualified female applicants learn of job opportunities (Andrews). This is also a hindrance at the company level. Large, mostly white male-owned construction fi rms have a propensity to do business with each other, and businesses with not as much capitaliza tion are left to bid on co mparatively minor jobs. This places difficulty on minority and women business enterprises, pushing them out of a vast amount of business opportunities. Several exceedingly talented women-owned construction firms lack access to capital for the purchase of equipment, labor and bonding. Recently, these minority and women-owned businesses have been constructing alliances with each other, an approach which boosts their general competitivene ss (Nesby 1999). Instances such as this are small steps in evening out the playing field and starting to overcome obstacles for women in the construction industry. External barriers such as discrimination by employers in selection and hiring, or harassment by co-workers can be tackle d to a certain degree by regulation and laws, however, internal barriers, which are socialized positions that lead women not to consider nontraditional occupations, must be dealt with th rough outreach programs targeted specifically towards women (Moccio 2006). The first step in co mbating these internal barriers is to educate young women. Current Recruitment Strategies Resoundingly, the recommendations for recr uitment of women in to the construction industry focused on getting into elementary a nd secondary schools and conversing with students about the prospects offered within the constr uction industry (Moore 2006). This starts by bridging the gap between educators and empl oyers. Hawaii’s Women in Technology Program studied the ways that construc tion corporations typically mark et their job openings and the correspondingly low rate of female applican ts who respond (Andrews). Through this study, they were able to form conclusions about re cruitment strategies. One strategy that was

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23 successful for Women in Technology was to deve lop partnerships with educators and guidance counselors, so that when employers were re cruiting, they had access to female students and graduates. Women in Technology developed relationships with em ployers that encouraged then to invest in talented women students through inte rnships and apprenticeships that led to full-time jobs. Women in Technology served as a clearinghouse, gathering resumes, and cultivating a communication network of women st udents, professionals and techni cal workers that served as a female counterpart of the “old -boys network” (Andrews). Another crucial area for recruitment that has been recognized is improved coordination and communication between secondary schools a nd post-secondary construction management degree programs (Moore 2006). Indisputably, at tracting women to the construction industry begins by educating them about pot ential construction careers as gi rls. Theresa Daytner, owner of Daytner Construction Group in Maryland, says that we need to stress the economic benefits of a construction career. “It is education and let ting people know about the options, but there is never discussion about money. As a young girl looking at career options, it was always about what I like, not about what I can earn” (Fishe r 2007). With construction occupations still deemed non-traditional careers for women, the majority of girls are not urged to investigate their carpentry skills, or contemplate a position as a project manager. Job shadowing and ‘Take Our Daughters and Sons to Work’ Day are model opportunities for a handson approach to the industry. In fact, this style of peer support or mentor protg re lationship seems to be essential to attracting and retaining wome n in the construction industry. Other hands-on type recruiting range anywhere from the National Associati on of Women in Construction’s Block Kids Competition to the Associated General Contractors of America’s Build Up! Program for fifth graders. These types of programs work consta ntly to spread the message about construction

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24 career opportunities through hands-o n activities. Theresa Dayt ner agrees, “We haven’t given our daughters the best exposure yet to the construction environment. We tend to be the ‘suits’, not out in the field. We need more handson opportunities” (Fisher 2007). Getting girls exposed to work in the field and exploring all of the options is key. Although the experience for girls is limited, there is already a system in place to support these hands-on programs for women who are preparing to enter the industry. The federal government has r ecognized the importance of mentoring to attract women to the construc tion fields, and has established the Women in Apprenticeships and Non-Trad itional Occupations (WANTO) grant. The Women in Apprenticeship and Nontraditional Occupations Ac t allowed the U.S. Department of Labor to give grants to community-based organizati ons to encourage the recruitment, training, employment, and retention of women in apprentices hip and nontraditional careers (Fisher 2007). The next obstacle in recruiting women fo r construction occupations is the actual recruitment to the apprenticeships and the succe ssful retention of women in these programs as well as in their future career s. The first way that Hawa ii’s Women in Technology program tackled this was by producing a flyer with a fam iliar image of a female construction laborer and the title “Female Applicants Wanted for Laborer Apprenticeship!” (Andrew s). The flyer also provided information about the starting and ending wages for apprentices, benefits, the application process and the date s applications would be accep ted. The Women in Technology program then assembled a fax list of over 200 organizations that assist women, cultural associations, day care providers, social servi ce providers, health se rvice suppliers, housing agencies, welfare and unemployment offices, grocery stores, health clubs, laundromats and beauty salons. All of these are places in wh ich women frequent, and ar e likely to hear about these new opportunities in constr uction. Women in Technology then developed a cover sheet for

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25 the fax that included an image of a female cons truction worker and explai ned briefly that women are underrepresented in apprenticeships, that a pprenticeships provide pa id on-the-job training with benefits, and that the majority of customar ily male apprenticeship fi elds offer considerably better pay than traditiona lly female lines of work. The cover sheet invited the recipient to copy, circulate and publicize the flyer and to inform prospective female candidates. A brochure was also put into an email and circul ated to a list of over 500 people particularly to the state and county Commissions on the Status of Women. The program drew up a press release to the local media with the title, “Female Apprenticeship App licants Sought by Labore rs’ Union”. To follow through with this recruiting strategy, the Ha waii Women in Technology program then offered recruitment and retention workshops and technica l assistance to employers and labor unions. This began with a 2-hour workshop consisting of a 15 minute welcome followed by a 15 minute group discussion on why women choose the trades and why women avoid the trades. This was followed by a 45 minute seminar on model recruitment and retention tactics. The workshop finished with 30 minutes for the action planning de velopment, where participants cultivated an action plan for their business to implement detail ed recruitment and retention strategies. During the closing 15 minutes of the workshop, particip ants presented their action plans. Women in Technology built upon the training workshops by offeri ng technical assistance to employers and labor unions throughout their recruitment of applicants. The Hawaii Women in Technology program has been able to accomplish remarkable expansion in the representation of women in apprenticeships and non-traditional employment by these methods. Overall, as a result of Women in Technology’s labors, 70 women were positioned in apprenticeships between September, 2001 and December, 2002, and the total number of women in registered

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26 apprenticeships statewide in Hawaii leaped ra dically, from 3.2% in 2001 to 5.1% in 2003, an increase of 59% (Andrews). Conclusions However, attaining sexual equality in the labor force involves more than just recruiting and training. The problem must be handled acco rding to the shifting demands of the workplace and the requirements of women. This may necess itate a transformation of the entire system (Moccio 2006). In order for th ese recruitment and training pr ograms to be successful, the industry must start changing itsel f. Diversifying companies requires new cultural competencies, such as ways to recruit and hire persons of color and women, lear ning how to find qualified minority and women-owned business enterprises, learning to use language that reinforces diversity, and making certain that conduct and operational practices are not discriminatory or exclusive. Furthermore, managers must become skilled in techniques for settling cross cultural and gender conflicts, and improve policies a nd practices that support diversity. Many government, state and municipal agencies are le gislating diversity by requiring minority and women business participation on th e development of projects (Nes by 1999). Legislation alone will not be enough. To give women these possibilit ies, they must be provided with support and encouragement for nontraditional choices at an early age. Women mu st be aggressively recruited into training programs with the aim of configuring the curriculum and skills training to assimilate them into high wage nontraditional em ployment (Moccio 2006). Then, once they are placed, the companies must cont inue to support these women, es pecially those with family obligations, by developing flexible work schedu les, allowing part-time or shared work arrangements, and possibly arranging childcare options (Andrews). Before women can be successfully recruited and integrated into the construction industry, the industry must change to

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27 actively seek women for job opportunities and creat e an atmosphere where new female recruits will be treated with respect. Unique Skill Sets by Gender Introduction Studies have shown that men and women perf orm differently on tasks. This difference can be attributed to a degree to their sex. Studies have also shown that women are employed in some ‘lighter’ construction trades and are not significantly present in other trades. What has not been studied is the relationship between the un ique gender skill sets and the placement of women in construction firms. The construction industry is historically male-dominated and changes at an extremely slow rate. The industry is also deep ly rooted with stereoty pical images of what a construction worker should look like and act like: a man. While other in dustries are approaching sexual equality, construction is lagging far behind. The first and foremost reason for this difference in velocity may be the lingering nega tive stereotypes toward women mingled with the traditional belief that construction is a ‘man’s job’. Gender stereotypes are present in many r ealms, including personality traits and intellectual achievement (Ortner, T. & Sieverdin g, M. 2008). In consideration of personality traits, men are regularly seen as more autonomou s, assertive, and competitive, whereas women are perceived as more sensitive, communicative, and tender-minded. These gender-based personality traits reflect and replicate the archet ypal social positions as the ‘male breadwinner’ and the ‘female caregiver’. In co nsideration of intellectual abilitie s, from most viewpoints, the male stereotype has the advantage. Men are gene rally seen as more intelligent, and generally estimate themselves as so. Gender based stereot ypes were most likely deve loped in earlier times, under different social situations, as a consequence of a gender-rela ted division of labor (Ortner, T. & Sieverding, M. 2008).

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28 Women are also plagued a phenomenon known as stereotype threat. Stereotype threat is believed to happen when a person experiences the th reat of substantiating a negative stereotype about their particular group (Jaušovec, N., & Jaušovec, K. 2008). Reminding women of the negative stereotype regarding women’s math skills, for instance, creates a “threat in the air”, which indicates the chance of the individual bei ng considered or evaluated in terms of the stereotype. This threat, and the anxiety it brings about, may rest rain individuals from performing to their fullest potential (Jaušov ec, N., & Jaušovec, K. 2008). Wome n in construction battle with stereotype threat everyday, with the belief that others think th ey are incapable. The purpose of this part of the research is to look beyond gender stereotypes and examine gender differences as they are relevant to cons truction. It will also address existing gender stereotypes and the effects that th ey cause in work situations. The study of gender differences is divided into three sets: (1) thos e skills typically used and related to work in-the-field (or to conduct physical work at the jobs ite), (2) skills and traits typically required for supervisory, management and leadership roles within the comp any, and (3) mathematical and technical skills required to perform work for the project. Physical Abilities Musculoskeletal differences Females inexplicably run a greater risk than males of work-related musculoskeletal disorders (Nordander et al. 2008) A study by Nordander et al. (2008) evaluated whether male and female workers, with the same repetitive job tasks, differed regarding the risk of disorders and physical or psychosocial experiences. Empl oyees in rubber manufacturing and mechanical assembly plants were studied. These industries were chosen because in both, groups of male and female workers worked alongside each other carrying out the same repetitive job tasks

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29 (Nordander et al. 2008). These t ypes of industrial jobs are often compared to the construction industry. It was found that functioning postu res and movements were analogous among both genders (Nordander et al. 2008). Females, howev er, had a higher number of reported disorders, especially involving disorder s of the neck and upper extremity. It is widely held that males, in general, are stronger than females. However, the women in this study showed significantly greater muscular activity, as compared to their overall strength (Nordand er et al. 2008). For females, muscle activity of the forearm extens ors was higher than 39% of the maximum exertion for a period of 10% of the workday. Correspondi ngly, the figure for males was 27%. Females also demonstrated less muscular re st in the forearm extensors. This may mean that their muscles had less time to recover following ea ch of the high-power applica tions (Nordander et al. 2008). Females, possibly more regularly than male s, are working in occ upations with greater risk for injury (Nordander et al. 2008). This study showed that females were twice as likely as males to leave the industry because of complaints of pain and injury. These occupations of greater risk may also be linked to earlier studies that ha ve revealed that lo w job-control and high job demands are connected with musculoskeletal disorders. Females have reported less jobcontrol, and more job-demands, than males, sugges ting that this may be a cause as to why they also report more muscular disorders. Such circumstances are common outcomes of highly constrained and controlled job ta sks such as the assembly line work examined here, which are more common jobs amongst females. Gender differe nces effecting work tasks can also be seen in activities outside of the job. Women typically spend more time doing household work, and have less time for recovery and exercise. De ficiencies in recovery during leisure time, specifically the lack of muscular relaxation, may amplify the risk of disorders. This is an especially prevalent issue for moth ers. In addition to rest and re gular exercise, it is recommended

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30 that the amount of time spent on such high-force work tasks should be lessened, by incorporating other, non-repetitive, job tasks to reduce the number of musculos keletal disorders (Nordander et al. 2008). Personal protection equipment and body types Women in the construction and manufactur ing industries have typically worn PPE (Personal Protection Equipment) designed for me n (Naso, M. 2006). Prev iously, boots, gloves, harnesses and additional gear were not readily obtainable in female sizes as the demand was low. Many women at that time were not employed in blue-collar jobs. According to the Bureau of Labor Statistics, women now embody 10 percent of the construction workforce and 30 percent of the manufacturing workforce in the United Stat es. Manufacturers are currently attacking women's sizing in two ways: creating entirely separate products for just for women or developing PPE that fits a wider range of sizes While both men and wo men contend with the same risks on the job, the lack of suitable equipment frequently heightens a woman's vulnerability to injury. "Most welding gloves, for example, are made in men's large or extra large sizes. It's not commonplace to find a supplier with small or extra small welding gloves," said Terri Piasecki, owner of Charm and Hammer, an on line supply store specia lizing in safety gear for women (Naso, M. 2006). "If a woman wears a welding glove that's too large, how is she going to handle anything? How is she going to pick up a tool prope rly?" Along with the decrease in dexterity, oversized gloves create real hazards to women working near equipment. “A glove that is too big easily can get caught in a conveyor belt or on a le ver, pullinga woman's hand with it,” Piasecki said. One new line of PPE for women is crafted by two female engineers and founded on a rock climber's harness. The new lin e is called ‘Ms. Miller’ and is distinct from a man's harness because it is adapted to hold a woman's center of gravity and the form of her

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31 hips. “Women in construction and manufacturing traditionally have tried to blend in; they are used to wearing men's equipment,” Piasecki said. She also added that numerous women did not want companies to think they had to acquire anything different for them; the women thought it would make them unmarketable. Piasecki said, "V ery little was said (abo ut PPE not fitting). They just put up with it because th ey wanted the job" (Naso, M. 2006). Manual dexterity Folk psychology suggests that women's fingers are nimble (Peters, M. & Campagnaro, P. 1996). However, this may not necessarily lead to the conclusion that they have greater dexterity than men. Modern experimental psychology su ggests that women perfo rm well on tasks that entail fine synchronization of muscles and excel in rapidity and accuracy of repetitive reactions (Peters, M. & Campagnaro, P. 1996). A study in 1993 stated that "women do better on precision manual tasks—that is, those involving fine-mot or coordination—such as placing the pegs in holes on a board". It could be possible that finger size itself has something to do with the precise dexterity of women rather than a difference in sex. In contrast, men are believed to do extremely well on tasks that entail "extensive mediation of higher processes as opposed to reflexive stimulus response connections". Men also s how a greater competitiveness when performing manual dexterity tasks, especially in tasks wh ere there is less importance placed on finesse and more on speed. Conversely, women were observed in manual dexterity tests as more cooperative in nature. Although it is said th at women’s fingers are more nimble, historically men have held positions such as jewelers and goldsmiths. Th ese occupations use tools to operate on their objects, involve immense precision and very minuscu le movement trajectories. These types of tasks that make very high demands of manual de xterity. Similarly, the most challenging human ability in terms of swift and precise movement, force modulati on, and sequencing are created by

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32 the playing of musical instruments. Traditionally in Western cultures, musicians have been men. It seems that as long as the variable of finger si ze is removed, the occupation is linked to more to social conventions than to innate differences in fine motor abilities of the sexes (Peters, M. & Campagnaro, P. 1996). Thus, reinforcing stereotype s rather than true abilities. The only real differences that may be deciphered are the differe nces in response to repetitive activities. Spatial abilities The strongest and most distinct sex difference is seen in spatial abil ities (Jaušovec, N., & Jaušovec, K. 2008). Spatial ability can be subdi vided into three categor ies: spatial perception, mental rotation, and spatial visualization. The largest difference betwee n the sexes in spatial abilities lies in tasks of mental rotation, in fa vor of males (McGlone, M. & Aronson, J. 2006). Tests of this nature typically re quire the taker “to visualize a st atic twoor three-dimensional target object from one of several different pers pectives and to determine whether the “mentally rotated” target object matches the shape of one or more comparison objects”. Tests developed in 1971 such as the Shepard and Metzler mental rotation paradigm and the Vandenberg Mental Rotation Test produced an outcome of approximate ly one full standard deviation of difference between the sexes, the greatest recognized sex difference of any cognitive ability. Of those scoring above average on the test, 75% were male and 25% were female. These statistics have empowered those who believe that the difference is due completely to ‘innate abilities’. For instance, Harvard University President Lawrence Summers attributed the lack of women in the math and science professorate to differences in “i nnate ability.” Conversel y, nearly all scientists familiar with the gender gap identify that it is so vast that it most likely entails a mixture of genetic and socialization theories to explain it. Over the last 30 years, the gap between men and women's scholastic and professional contact with visual–spatial tasks has closed swiftly.

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33 However, the gap in their achievement on tests of this type has stayed ra ther stable (McGlone, M. & Aronson, J. 2006). What part might the st ereotype of female visu al–spatial incompetence play in this spatial abilities gap? A study performed in Germany, aimed “to analyze the effects of gender and gender stereotype priming on performance of a mental ro tation task” (Ortner, T. & Sieverding, M. 2008). They concluded that the effect of ge nder priming on test outcome was considerable, whereas the key effect of gende r was not substantial. “Within this study, women were clearly able to perform the same level of mental ro tation as men with low effort” (Ortner, T. & Sieverding, M. 2008). Howeve r, another possible outcome may have come out of this: women must struggle with the likelihood that poor perf ormance will validate a negative stereotype about their spatial abilities (McGlone, M. & Aronson, J. 2006). Women may then be battling two separate objectives, one which is the actual test and one which dist racts them from the test and turns their attention to ev aluative concerns. This diversion in their attention fr om the actual test may negatively impact their performance (McGl one, M. & Aronson, J. 2006). Alternatively, one could hypothesize that those with higher abilities, of both genders, to some degree compensate for their substandard skills by intensif ying their level of attention put forth toward the task (Jaušovec, N., & Jaušovec, K. 2008). Th is, and other research, calls into question the naive presumption that biological differences completely rationalize the differences in performance outcomes of spatial tasks (McGlone, M. & Aronson, J. 2006). Leadership/Management Abilities Emotional intelligence – recognizing emotions Emotional intelligence is “the ability to recognize emotion, reason with emotion and emotion-related information, and process emotional information as part of general problem

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34 solving” (Jaušovec, N., & Jaušovec, K. 2008). Recent studies have found that females exceed males on tests of emotional intelligence. Agai n, both genders to some degree compensate for their lesser abilities by increasing their level of at tention; for females with spatial rotation tasks, and for males in emotional tasks (Jaušovec, N., & Jaušovec, K. 2008). Communication and verbal abilities Research shows that women are typically better in areas conc erning communication and verbal abilities. This is may also be a part of the stereotypi cal view about women talking more than men. In an ancient Sanskrit book, nine shares of talk were given to women and one to men, symbolizing what is most likely one of the firs t written accounts for female advantage in verbal ability (Jaušovec, N., & Jaušovec, K. 2008). Cu rrent studies propose that females exceed males in some, but not necessarily in all, sections of verbal abilities. Communication is very important in positions involving supervisi ng other workers and all types of management and leadership positions. Supervision Supervision depends greatly on a woman's work -related status and position (Ortner, T. & Sieverding, M. 2008). In contrast the supervision of male work ers principally reflects their ability. The association suggests that supervision in men's o ccupations are considered and adapted on the foundation of performance, while women must be able to wield influence over supervisory practices by way of prestige (Ortner, T. & Sieverding, M. 2008). Group behavior Research shows that the gender composition, or the sexes which make up the group, have a greater affect on women’s behavior than men’s (Taps, J. & Martin, P. 1990). The difference in how women are perceived and responded to with in the group may be attributed to whether

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35 they give internal or external accounts. “ Internal accounts give credit to one's own knowledge, experience, or skills as a reason or explanation for one's behavior, whereas external accounts give credit to others, such as teachers, experts, books, media, and so on.” Reports crediting one's own experiences, or internal acc ounts, can show that the member of the group is knowledgeable and should be paid attention, therefore acceptable or even admirable. Conversely, such accounts may also be regarded as conceited and condes cending, particularly when given by a low-status group member, in this instance, a woman. These inte rnal accounts of women may then be seen as efforts to take over, and theref ore become irrelevant and unaccep ted. The way that internal and external accounts are perceived also depends to a great extent on the total composition of the group, not just the reaction of the individual. One study found that “(a) a solo woman in an otherwise male group is most infl uential and well liked when sh e gives external attributional accounts, (b) a woman in an all-fe male group is most influential and well liked when she gives internal accounts, and (c) a woman in gender-bala nced groups is comparably influential and well liked when she gives internal or external accounts”. The study also found that a solo woman in an otherwise male group, which is typical of construction, has little sway on coworkers and is not popular among the group if they give internal accounts. These groups seemingly develop a normative configuration that commends and suppor ts women who give recognition to others in external accounts, but overlooks and rejects women that credit themselves. Again, in this instance, a woman may be seen as conceited and condescending to other group members. In the compositional group, however, men are impacted by, and like, women who present external accounts. Those accounts are perceived as legitimate. “It is not only what women do or say that influences their male co-workers but what they do or say in the context of variously gendercomposed groups” (Taps, J. & Martin, P. 1990)

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36 The gendered nature of occupations gives norma tive and legitimacy partiality to men and develops a burden for women who are forced to pr ove themselves (Taps, J. & Martin, P. 1990). Tailoring comments to give acknowledgment to ex ternal sources can neutralize differences between the minority and majority genders of the group and tailoring comments toward the audience can be employed as a tactic to improve effectiveness. While it may appear wrong that women must vary their choice of accounts to their audience to be accepted, this is not an unusual occurrence for low-status members in groups (Taps, J. & Martin, P. 1990). Overall, equally composed groups are best for women, but are rare in construction work. In other industries, and hopefully in the future of construction, group administrators can take these matters into account and create task groups in ways that do not inad vertently put women at a disadvantage from the start (Tap s, J. & Martin, P. 1990). Leadership There are both advantages and disadvantages for women as leaders (Eagly, A. & Carli, L. 2003). Most of the disadvantages come from ma sculine defined roles or roles that are maledominated. The traditional female role does not f it into these masculine positions easily and is met with strong prejudice. Because of this, women are forced to perform beyond the expectations of the normal competence level wh ile still reassuring othe rs with their gender appropriate female behavior. This can be very difficult to accomplish and also may hinder women from achieving recogniti on for high ability or outstandi ng achievements. Given this background, women may tend more toward transf ormational leadership because it reflects expected gender roles for women, including supportiv e and considerate behavi or toward others. “Transformational leadership entails establishing oneself as a role model by gaining followers’ trust and confidence” (Eagly, A. & Carli, L. 200 3). The case that women are more effective

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37 leaders is not direct— that is, wo men, more so than men, exhibit lead ership styles that have been linked with effectiveness (Eagly, A. 2007). Previous studies have shown that there has been a shift toward women leaders (Eagly, A. & Carli, L. 2003). This may be attributed to the gradual breaki ng down of barriers and disadvantages for women. It may also be because of the increase in number of women in the labor force. Women themselves are changing; self-reports of assertiv eness, dominance, and masculinity, and the value that women place on j ob attributes such as freedom, challenge, leadership, prestige, and power ha ve all become more similar to those of men. Leadership roles have also changed. The role of ‘manager’ is no longer solely ge nderized as being male. With increasing numbers of women lead ers, organizations have changed. They are now driven more “by results than ‘old boy’ networks, they reward talent over gender and present a more level playing field than do traditional organizations”. Women succeeding in these organizations are symbols of innovation and progressive cha nge (Eagly, A. & Carli, L. 2003). Technological/Mathematical Abilities Computer literacy Computer related activitie s are stereotypically linked to the male gender. A study performed in 1997 found that males experience c onsiderably more successful computer-related results than females across all organizational jobs with the exception of clerical work (Harrison,A. et al. 1997). To make matters worse, males' achievement with computers may additionally strengthen the sex orientation of computing occupa tions, thus discouraging females even further from successful endeavors. Excludin g clerical workers, females were concluded to be more fearful of computer work, had less opti mistic participation, a nd believed computers to be more controlling. These pess imistic feelings may hinder their use of the computer. Females also stated that they used all software applicat ions and graphics consid erably less than males.

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38 This may also hinder their success because l earning curve theories imply that repetition frequently enhances performance. Females’ fears about computer usage may lead to lower beliefs of their own abilities a nd thus may lead them to expect less of themselves. In the 1997 study, females conveyed significantly poorer comput er self-efficacy than males (Harrison,A. et al. 1997). These conclusions have implications for bot h females and organizations (Harrison,A. et al. 1997). First, females must be conscious th at performance of computer-related activities may establish yet one more barrier to their work-related success. Fe males must knowingly cope with the apparent male stereotype of computing. Second, organizations must also be sensitive to the evidence that a lack of expertis e in computing may impede fema les in responsibility, pay, and professional advancement. Organizations should develop methods to conquer such obstructions (Harrison,A. et al. 1997). Mathematical abilities A widespread stereotype is that men perform better than women in mathematical abilities. It actually depends on the test itself (Eriksson, K., & Lindholm, T. 2007). Over the past years, a mounting body of research has confir med that gender differences in math abilities may be produced, propagated, or re moved by variables in the test c ondition itself. In particular, research has shown that the establishment of the negative stereotype of wo men’s abilities in the field of math can lead women to underachieve on math tests. When participants were notified beforehand that either the test had been shown to generate gender differences or that it had been shown not to generate such differences, men achieve d higher scores than women. The results demonstrated that when notified that the test had revealed gender diffe rences, women performed

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39 more inadequately than men. The gender rele vance manipulation altered men’s performance more than women’s (Eriksson, K., & Lindholm, T. 2007). In a study conducted by Schmader, results s howed that the negativ e stereotype threat effect on women’s math test scores only infl uenced those women who deeply identified with their gender (Eriksson, K., & Lindholm, T. 2007). According to Schmader, the justification of this effect of high gender recognition may be th at women who are exceed ingly identified with their gender are further encouraged to sustain a positive image of that identity than lower identifiers. Consequently, highly gender iden tified women possibly will experience greater threat, and consequential impairments at the prop osition that their ‘in-grou p’ is substandard to other groups. “While both groups of women thus to an equal extent may endorse the negative stereotype of women’s math abilities, and recogni ze a threat of confirming a negative stereotype about women’s math abilities, those high in gend er identification can use their strong, general belief and their experience of support for this belief as a protection against these expectancies.” Still, if a woman who id entifies less with their gender is more doubtful of their rights in general, they do not have these means of prevailing over the pressure of th e threat and their performance will decrease as a result (Eriksson, K., & Lindholm, T. 2007). The results of the aforementioned study sugge st that the gender identity relevance manipulation made these wome n more cautious and meticulous on any given problem, or instead, that they experienced more struggles solving each problem because their cognitive abilities were preoccupied (Eriksson, K., & Li ndholm, T. 2007). As mentioned before, the phenomenon is known as stereotype threat This threat, and the inti midation it brings about, may hinder individuals from performing to their capability (Eriksson, K., & Lindholm, T. 2007).

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40 Conclusions The greatest differences between the sexes were found in areas of muscular abilities – in favor of men, in emotional intelligence – in fa vor of women, in communication and verbal abilities – in favor of women, in group behavior based on gender composition – in favor of men, in leadership – in favor of women, and in comput er literacy – in favor of men. Results from the other studies concluded that th ere was no significant difference in ability between males and females with gender based stereotypes aside. Many of the differences that were significant could have logically been hypothesized. For example, it is well known that males, in general, are stronger than females. Other main differences he lp to point out ways in which behavior may be modified to fit the situation; such is the cas e with group behavior based on gender composition. However, the more intriguing conclusions ar e those which provide proof toward gender equalities, thus negating wide-s pread gender stereotypes. These include the equal performance of women on spatial and mental rotation tasks. With an industry-wide shortage of skilled workers, this may be a case for recruiting fema le equipment operators, especially since this position does not require excessive physical stre ngth. There is no reasoning left for placing women in ‘lighter’ occupations on the basis of gender abilities, when they possess the same skills as men do. Some employers even report that they prefer to hire women, stating that they “drink less” and are more responsible. With equal, or at least comparable, skills, and a more dependable nature, females may actually be able to boost construction productivity even though they are physically weaker. Furthermore, women may make better construction managers because of their greater abil ity in emotional intelligen ce and communication, and their propensity toward the transformational leadersh ip style. The reasoning for the absence of women in the industry may soon lie in women’s pr eferences toward femini ne occupations, rather than a barrier of industry stereotypes. The diffe rences between male and female workers are not

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41 as vast as was once thought. Once stereotypes are put aside, construction may be able to develop a more diverse and productive workforce. Personality Traits by Gender Background Research on gender differences was initiated by scientists who suspec ted that individual distinctions of traits were biol ogically determined (Feingold, A. 1994). They also believed that findings of gender differences suppo rted this assertion. Some of the first discussions of gender differences began with the conclusions from Maccoby and Jacklin's (197 4) research of sex differences in cognition, temperament, and soci al behavior (Feingold, A. 1994). Maccoby and Jacklin applied the previously widely-used narrative method of review. This means that the studies were evaluated by area, then the significance or non-signi ficance of each difference was recorded by study, and deductions were made subjectively from both the quantity and the uniformity of significant gender differences. Maccoby and Jacklin's study found males to be more assertive (dominant), more aggressive, and less anxious than females. No sex difference was found in their studies for self-esteem. A person’ s locus of control was concluded to fluctuate by age, with a gender difference (greater male in ternality) coming out only during college years. Other earlier studies found that females scored higher than males on ego development but that the difference diminishes with age. This fi nding suggests that the sex difference may be a product of prior female maturation in ego deve lopment (Feingold, A. 1994) The causes of sex differences may be the most difficult aspect to determine. Proximal Causes Biological model The biological model speculates that observe d gender differences in personality test scores “reflect innate temperamental differe nces between the sexes” (Feingold, A. 1994).

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42 Modern research has proposed that there is a strong biological founda tion underlying individual dissimilarities in personality traits. A study by Zuckerman conducted in 1991, implied that gender differences in the traits of dominance and aggression may be pr oduced by biological sex differences in gonadal hormones (Feingold, A. 1994). An earlier study in 1987 also hypothesized that sex differences in chromosome s may make women more prone to depression than men. “Women have two X chromosomes, in comparison with one for men, and major affective illnesses may be caused by a mutant gene on the X chromosome” (Feingold, A. 1994). In these studies, a greater female susceptibility to depression would be discernible in higher scores for women than for men on assessments of depression, anxi ety, and neuroticism. Socio-cultural model The socio-cultural model of gender differences suggests that social and cultural factors create gender differences in pers onality traits in a direct mann er. Studies by Eagly in 1987 and Eagly & Wood in 1991, hypothesized that sex differen ces in social behavior come from gender roles, which state the behaviors that are suitab le for males and females (Feingold, A. 1994). One socio-cultural model is the expectancy model This model insists that social and cultural factors propagate in gender stereotypes. This in turn, causes sex differences in personality traits; as holders of stereotypical beliefs treat others in a manner that re sults in others conforming into compliance with the prejudices of the perceivers Self-concept may also influence expectancy outcomes. For example, if “assertiveness is a tra it seen to be characteristic of men, then people may respond to men in a manner that causes men to first internalize assertiv eness as part of their self-concept and then to behave assertively to bri ng their behaviors in line with their self-image” (Feingold, A. 1994). Another example of a socio-cultu ral model is the artifact model The artifact model suggests that socio-cultural f actors (e.g., gender stereotyping) re sult in men and women holding

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43 different values about the importance of possessi ng various traits (Feingo ld, A. 1994). “Women may view nurturance, for example, as a very positive characteristic, and social desirabilityrelated biases may result in women reporting themse lves to be more nurturant than they are. Men, by comparison, may have been inculcated with the belief that nurtu rant males are "wimps" or "sissies" and may underreport their level of nurturance” (Feingold, A. 1994). Distal Causes Current gender differences may be a conse quence of socio-cultural factors that are a remnant of bygone eras. Social ro les, based primarily on the distribution of work tasks, may have developed in preindustrial times as a result of phys ical differences of the sexes, which were far more significant then than in the present te chnological age (Feingold, A. 1994). These physical differences pertain to greater ma le size and strength as well as anatomical differences involving aspects of reproduction. Accordingly, traditional male and female work roles were assigned. The gender associations of work tasks in the preindustrial age may have produced gender differences in personality traits. Conclusions Overall, recent research found males to be more assertive and have slightly higher selfesteem than females, although the effect size was very small (Feingold, A. 1994). Females were rated higher than males in extraversion, anxiety, trust, and especially high in tender-mindedness (e.g., nurturance). There were no significant diffe rences between the sexes in social anxiety, impulsiveness, activity, ideas, locus of control, a nd orderliness. Gender differences in personality traits were commonly steady across ages, years of data collection, educational levels, and nations (Feingold, A. 1994).

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44 Women in the Construction Trades Job Satisfaction Because individuals usually perform best at jobs or occupations that satisfy them, it is important to examine women’s satisfaction with cons truction jobs. It is a fairly safe assumption to say that women will strive to succeed as long as they are satisfied with the work. Research has revealed that pay, benefits, a nd job security are most essential to women in their occupations (Dabke, S. et al. 2008). Although tradeswomen appear to be satisfied with the nature of work in the construction trades, this is not the case in te rms of pay, benefits, and job security. Research found that women liked the nature of work in car pentry and were proud of building a structure as a result of their efforts. They took great pride in projects on which they worked and spoke highly about those projects. Many of them mentioned helping or seeing their fathers and uncles do carpentry as a child and thus chose carpentry as a career. The opportunity to learn new things, adequacy of tools, quality of equipment and machinery for job performance, and supervisory support were found to be important, yet their satisf action is relatively lower in these aspects of work. Women in construction trades were most content with personal protective equipment, the ability to execute work, comple tion of a whole and identifiable piece of work, job training, opportunities to develop skills and abilities, and opport unities for challenging work. They were least satisfied with separate and hygienic sa nitary facilities, understanding of family responsibilities by management, support from ma nagement during maternity or other medical situations, job security, and wo rk benefits. Women reported dissa tisfaction with opportunities for promotion. They also expressed a desire to quit th e trades and reported low levels of satisfaction with opportunities and supervisi on. They were attracted to trad es primarily because of higher wages; some had worked at administrative jobs but joined trades because of pay and union benefits. Coworker support or treatment was not important to women, and they were satisfied

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45 with people on the job. Overall they wanted to work in the trades and establish themselves so that the next generation of women would be better off (Dabke, S. et al. 2008). Representation Women in the trades increased by 13.8% from 1995 to 2001 (Dabke, S. et al. 2008). In 2004, women comprised 6.4% of the construction mana gers, 11.7% of the civi l engineers, and an overall 2.5% of the total employment across various trades. Thus, construction remains a nontraditional occupation for women, as women co mprise less than 25% of those employed in this industry (Dabke, S. et al. 2008). The most recent statistics produced by th e Bureau of Women, a division of the United States Bureau of Labor Statistics (Fig. 2-1), show the representation of women in each of the respective construction trades. These trades are considered non-traditional occupations for women, since they are comprised of less than 25 % women. Overall, the Bureau of Women has noted 153 occupations as nontraditi onal (Menches, C. & Abraham, D. 2007). Of those, 33 are construction-related professions. Of the 33 occupa tions, 25 are related to the construction trades. These trades consist of many of the traditional field labor positions, such as carpenters, plumbers, electricians, and equipment operators. Over 75% of the trades employ fewer than 5% women. Almost 10% reported employing no women at all. Only paperhangers and woodworkers employ more than 10% women (Mench es, C. & Abraham, D. 2007).

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46 Figure 2-1. Percentage of wo men employed in construction tr ades. (Adapted from: United States Bureau of Labor Statistics. (2007). Women in the labor force : A databook Washington, DC: U.S. Dept. of Labor, U.S. Bureau of Labor Statistics.)

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47 Comparison to similar occupations In 2006, the Bureau of Labor Statistics reported that 3.1% of all employees in the construction and extraction occupations were wome n (Table 2-1). Similar construction-related occupations of Architecture and E ngineering reported that 14.5% of all employees were women. These proportional differences can be seen graphically in Figure 2-2. The highest concentrations of women in Arch itecture and Engineer ing Occupations were in Industrial Engineering (inc luding Health and Safety) with 22.6% of all employed (174,000 out of 2,830,000 total employees in Architecture and Engineering Occupations), followed by Architects (except Naval) w ith 22.2% of all employed (221, 000 out of 2,830,000 total employees in Architecture and Engineering Occupations) (T able 2-1). The highest concentrations of women in the Construction and Extraction Occu pations were in Construction and Building Inspection with 8.8% of all employed (102,000 out of 9,507,000 total employ ees in Construction and Extraction Occupations), followed by Painters (Construction and Maintenance) with 7.7% of all employed (713,000 out of 9,507,000 total employees in the Construction and Extraction Occupations).

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48 Table 2-1. Employed persons by detailed oc cupation and gender, 2006 annual averages (Numbers in thousands). (Source: United St ates Bureau of Labor Statistics, 2007) Occupation Total Employed Percent Women Architecture and engineering occupations 2,830 14.5 Architects, except naval Aerospace engineers Chemical engineers Civil engineers Computer hardware engineers Electrical and electronics engineers Industrial engineers, incl uding health and safety Mechanical engineers Drafters Engineering technicians, except drafters Surveying and mapping technicians 221 110 70 304 80 382 174 322 181 396 96 22.2 13.1 17.1 11.9 16.2 7.7 22.6 5.8 21.8 20.6 9.9 Construction and extraction occupations 9,507 3.1 First-line supervisors/managers of construction trades and extraction workers Brickmasons, blockmasons, and stonemasons Carpenters Carpet, floor, and tile in stallers and finishers Cement masons, concrete fini shers, and terrazzo workers Construction laborers Operating engineers and ot her construction equipment operators Drywall installers, ceiling tile installers, and tapers Electricians Painters, constructi on and maintenance Pipelayers, plumbers, pipefitters, and steamfitters Roofers Sheet metal workers Structural iron and steel workers Helpers, construction trades Construction and building inspectors Highway maintenance workers 976 244 1843 279 107 1693 451 295 882 713 662 242 125 59 132 102 103 2.6 1.6 2.4 2.4 0.7 3.7 1.7 2.9 1.9 7.7 1.8 1.1 3.1 2.2 6.2 8.8 3.8

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49 A Men 85.5% Women 14.5% Men Women B Men 96.9% Women 3.1% Figure 2-2. Comparison of repres entation of women in construc tion and extraction occupations versus women in architecture and engin eering occupations. A) Proportion of women in architecture and engineering occupations (2006). B) Proportion of women in construction and extraction occupations (2006). (Adapted fro m: United States Bureau of Labor Statistics. (2007). Women in the labor force : A databook Washington, DC: U.S. Dept. of Labor, U.S. Bureau of Labor Statistics.)

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50 Women in the Rinker School In the last fifteen years, the Rinker School ha s seen an increase in female students from 25 enrolled in 1992 to 95 enrolled in 2007, i.e ., the number of women enrolled has nearly quadrupled (Fig. 2-3). The overall proportiona l increase was only 8%. There is also a significant difference between the gender composition of the other majors w ithin the College of Design, Construction and Planning (DCP) when compared to the School of Building Construction. Other majors of the College of DCP are comprised of 51% women (479 enrolled) and 49% men (456 enrolled) as compared to 15% women (95 enrolled) and 85% men (557 enrolled) in the Rinker School (the majority of women in the Rinker School are enrolled in the Graduate Program). Other majors in the College of DCP also follow closely with the overall gender composition of the University of Florida (Fig. 23 & Fig. 2-4). The Engineering College has a gender composition that is similar to the Rinker School. Its programs are closely related to construction occupations, non-tra ditional occupations for women (Fig. 2-4). The Engineer ing School is still closer to the gend er composition of the University as a whole, with 21% female students and 79% male students, and has a higher overall enrollment of women (1,510 women and 5,606 men enrolled).

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51 A Male 557 85% Female 95 15% Male Female B 311, 93% 25, 7%C 456, 49% 479, 51% Figure 2-3. Comparison of represen tation of women in the M.E. Rinker, Sr. School of Building Construction to enrollment 15 years prior a nd other majors. A) Total enrollment in Rinker School of Building Construction (2007). B) Total enrollment in Rinker School of Building Construction (1992). C) Total enrollment in other majors in the College of DCP (Adapted from: University of Florida, (2008). UF Factbook: Enrollment. Retrieved November 4, 2008, from University of Florida, Office of Institutional Planning and Research Web site: http://www.ir.ufl.edu/factbook/enroll.htm)

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52 A Male 557 85% Female 95 15% Male Female B 5606, 79% 1510, 21%C 24619, 47% 27648, 53% Figure 2-4. Comparison of represen tation of women in the M.E. Rinker, Sr. School of Building Construction to enrollment of engineering majors and the University of Florida. A) Total enrollment in the Rinker School of Building Co nstruction (2007). B) Total enrollment in Engineering at the University of Florida (2007). C) Total en rollment in the University of Florida (2007). (Adapted from: University of Florida, (2008). UF Factbook: Enrollment. Retrieved November 4, 2008, from University of Florida, Office of Institutional Planning and Research Web site: http://www.ir.ufl.edu/factbook/enroll.htm)

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53 CHAPTER 3 METHODOLOGY Introduction This research was undertaken to examine th e perceived trends of women in construction in the state of Florida with regards to recruitm ent practices, placement within firms on the basis of gender, perceived task performance abilitie s and gender-based person ality traits. It was decided that the best way to co llect the needed information was a survey of the industry. The survey was then devised using findings from the literature review. The first revision of the survey was developed by the researcher and submitted for review by Dr.Hinze, committee chair. The survey was also tested by having friends of the researcher fill it out. The survey evolved through several such iterations. Potential recipients of the survey were then considered and a list of contact information was compiled. The decisi on was made to send the surveys to contractors of all types, including general contractors, design-builders, co nstruction management firms, and subcontractors. Survey Questionnaires Designed A survey was designed to obtain qualitative and quantitative information on trends of women in construction. The beginning of the su rvey sought demographic information about the construction company being surveyed, so that tre nds related to such aspects as volume of work subcontracted, size of the firm, type of firm, gender composition of the workplace, and position and gender of the survey respondent, could be assessed. The second section of the survey identified the specific positions within the company in which women were employed. This section was divided into office positions, field su pervisory positions, and trades positions. The second part of the survey also inquired about whether gender was considered when work was assigned to new hires. The object ive of the third part of the su rvey was to determine if the

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54 company had any specialized recr uitment program or effort in place for the hiring of women or any particular recruitment practic e against the hiring of women. Th e fourth section of the survey questionnaire was designed to record the obs ervations of how well women performed on workrelated skills and tasks when compared to their male counterparts. The tasks and skills tested in this section were developed from the informati on obtained through the literature review. The tasks and skills were described in a Likert-typ e fashion; for example, “women perform much worse” = “-3”, “women perform worse” = “-2”, etc. This section was al so designed to collect additional information on situations that relate to the skills and tasks studied, such as complaints of musculoskeletal injuries or pains by women, whether companies purchase and supply PPE specially made for women, observations of women’ s interaction in peer groups, and productivity observations. This part of the survey sought both quantitative and qualitative information. The fifth portion of the survey was designed with a similar Likert-type ranking system based on the degree to which personality traits are portrayed in employees. The personality traits used were based on those identified in the literature review. The final portion of the questionnaire dealt with the observations of women in the constructi on trades. This section asked the respondents to give their perceptions on the suitability of women in construction trades; if they are more suited or less suited for some trades than others. Sample Selection The sample selection used in this stu dy consisted of construction management and supervisory positions, along with other upper management positions. It was decided to send the surveys to companies that had attended an M.E. Rinker, Sr. School of Building Construction Career Fair. The contact information was gather ed from Career Fair materials so that only companies that were actively recruiting and have some type of company recruitment program in

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55 place were included in the survey population. The respondents represented a variety of construction companies. A total of 212 surveys were dispersed electronically. At this point in the study, an opportunity pr esented itself to survey graduate students of the M.E. Rinker, Sr. School of Building Construc tion. They were given the survey during class and asked to only answer the applicable ques tions. A total of 62 student surveys were conducted. Surveys Conducted The research plan for the industry survey consisted of an email message explaining the study and containing a link to direct the participant to the online survey. The student surveys were manually conducted during a graduate-level cl ass with an enrollment of 65 students. The following procedures were used to collect the data for this study: 1. Obtained the list of attendees of the M.E. Rinker, Sr. Sc hool of Building Construction Career Fairs. The list included useful info rmation such as a contact person and email address. 2. Survey recipients were 212 professionals in the industry who had attended an M.E. Rinker, Sr. School of Building Construction Career Fair. Surveys were distributed by email. Of the 212 emails sent out, 13 emails were returned as undeliverable. Within 48 hours, eight respondents ha d completed the survey. 3. A follow-up email reminding the contacts of the survey was sent 2 days after the initial distribution. Survey recipients who did not respond to the first request were asked to please respond. Those who had already respon ded were thanked for their assistance. Following this email, 29 more indi viduals responded to the survey.

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56 4. One week after the first email message was se nt, a third and final email was sent to the potential respondents. They were again enco uraged to complete the survey. Nine more individuals responded to this email, re sulting in a total of 46 respondents. 5. Conducted the student survey during a graduate class, of which 62 surveys were completed out of 62 distributed. 6. Obtained data from both surveys was compiled to be reviewed and analyzed. Data Analysis The results of the surveys were first analy zed by evaluating the fr equency distributions. Statistical tests for correlations between data co llected were then perfor med using the Statistical Package for the Social Sciences (SPSS). The results of these analytical a pproaches are presented in Chapter 4.

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57 CHAPTER 4 RESULTS Survey Response Rate The findings of this research are based on a total of 108 complete d surveys that were received. A total of 261 surveys were disper sed, representing a res ponse rate of 41.4%. In the student survey, 62 surveys were manua lly distributed and 62 surveys were received, representing a response rate of 100%. In the industry professional survey, 212 surveys were electronically distributed. Of those, 13 were returned as undeliverable leaving a total of 199 industry professional surveys distributed. There were 46 responses to the industry professional survey, representing a response rate of 23.1%. The findings will be presented for each of the topic areas of the survey based upon the total grou p of respondents, the position or experience in the industry of the respondents, a nd by the gender of the respondents. Respondent Demographics The first part of each survey was designed to collect demographic information about the respondent and the company being surveyed. Many business sectors were represented by the respondents (Figure 4-1). The resu lts show that 64 of the responde nts that were surveyed did at least some work in the commercial sector. Note that respondents were asked to mark all of the industry sectors that applied, thus the sum of the total number in each sector may be greater than the number of respondents. Those sectors categ orized as “other types” included government, healthcare, education, sports/event venues, site development, hist orical restoration, sustainable construction, institutional, a nd entertainment type projects. Many business classifications were represented by the resp ondents (Figure 4-2). The results show that the most common type of empl oyers surveyed were gene ral contractors with 50 respondents, and construction management firms w ith 32 respondents. Again, it should be noted

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58 that respondents were asked to mark all that applied, thus the sum of the total number in each classification may be greater than the number of respondents. Those bus iness classifications noted as “other type” included integrated real estate services, developer, owner, architecture/engineering design servi ces, consultants, and design firms. Commercial 64 50% Industrial 14 11% Heavy Civil / Transportation 10 8% Residential 26 21% Other types 13 10% Figure 4-1. Types of project s performed by respondents. General Contractor 50 42% Design Builder 19 16% Construction Management Firm 32 27% Subcontractor 9 8% Other type 8 7% Figure 4-2. Types of empl oyers of respondents.

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59 Respondents were also asked a bout the percentage of work that the company subcontracts out to other businesses (Figure 43). Of the 74 responses to th is question, 64.9% subcontracted over 75% of the work to be performed on a project and 8.11% responded that they selfperformed all the work. 0%, 6 1% to 20%, 7 21% to 40%, 8 41% to 75%, 5 76% to 90%, 19 91% to 100%, 29 Figure 4-3. Percent of work subcontracted. Respondents of the survey were asked to indicate their position within the company (Figure 4-4). Students represented 58% of all survey respondents and industry professionals represented 43% of all survey resp ondents. Of the industry profe ssionals, 3% were presidents or CEOs, 9% were vice presidents, 10% were project managers, and 20% were in other positions. Those positions categorized as “other” incl uded director of huma n resources, business development, recruiter, marketing manager, office engineer, proj ect engineer, project coordinator, operations manager, executive assistant, and owner.

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60 Student 62 58% President/CEO 3 3% Vice President 10 9% Project Manager 11 10% Other position 22 20% Industry Professional 46 43% Figure 4-4. Construction indus try position of respondents. Students, instead of indicating the position within the company, were asked to indicate the amount of experience, if any, that they had obtained in the constr uction industry (Figure 4-5). Of the students surveyed, 33.9% res ponded that they did not have a ny past experience nor are they currently working in the construc tion industry. Of the remaining 66.1% that responded that they did have experience related to the construction industry, 38% ha d two to twelve months of construction-related experience and 6% had more than six ye ars of construction-related experience. Respondents completing the survey were also as ked to indicate whether they were male or female. Of all the surveys conducted, 62 respon dents were men and 46 respondents were women (Figure 4-6). Of the industry professional respondents, 18 were men and 28 were women (Figure 4-7). Of the student survey responde nts, 44 were men and 18 were women (Figure 48).

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61 No 33% 2 to 6 months 25% 9 to 12 months 13% 15 to 18 months 5% 22 to 24 months 3% 30 to 48 months 10% 60 months 3% 72 months 2% more than 6 years experience 6% Yes 41 66% Figure 4-5. Students’ amount of constr uction experience. Male 62 57% Female 46 43% Figure 4-6. Gender composition of industry pr ofessional and student survey respondents.

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62 Male 18 39% Female 28 61% Figure 4-7. Gender composition of industry professional respondents. Male 44 71% Female 18 29% Figure 4-8. Gender composition of student respondents. To determine the composition of each respondent’s company workforce, questions were asked about the number of field employees (m anual workers), the number of home office personnel and salaried employees, and how many of those employees were women. Since each

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63 of these questions had two parts, partial respons es were not included in the analysis. Reponses of zero (or no responses) total field employees or zero total home office personnel and salaried employees were also not included, because thos e responses do not provide any information on the proportions relative to the number of women employed. In reference to field employees, the number of total field employees ranged from one to 500, with a mean of 91.8 field employees (Figure 4-9). Nine respondents reported that they did not have any field employees. The number of women field employees ra nged from zero to 200, with a mean of 9.05 women field employees. In reference to home office personnel and salaried employees the total number of employees ranged from one to1,900, with a mean of 77.4 employees (Figure 4-10). Three respondents reported that they did not have any home office personnel and salaried employees. The number of women home office personnel and sa laried employees ranged from zero to 250, with a mean of 16.5 women employees. 0 50 100 150 200 250 300 350 400 450 500 550 051015202530354045505560Number of Employees Number of field employees (manual workers)? How many are women? Linear (Number of field employees (manual workers)?) Linear (How many are women?) Figure 4-9. Numbers of field employees.

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64 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 051015202530354045505560657075Number of Employees Number of home office personnel and salaried employees? How many are women? Linear (Number of home office personnel and salaried employees?) Linear (How many are women?) Figure 4-10. Numbers of home office personnel. A statistical analysis was performed to evalua te if there were corre lations between aspects of employer demographics. Correlation tests that were performed can be found in Table D-1. Correlations with a level of significance of 0.05 or less were considered to be statistically significant, while those with a level of significance between 0.05 and 0.10 were considered to have a tendency to being significant. The fo llowing results have a tendency toward being significant: Larger companies have a greater proportion of female field employees (Figure 4-11). As the total number of home office personne l and salaried employees increases, the proportion of women home office em ployees decreases (Figure 4-12). Subcontractors have a smaller percentage of women home office personnel and salaried employees than do general contractors. The greater the amount of work that is s ubcontracted, the greater the proportion of women home office personnel and salaried employees.

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65 Firms that do commercial projects have a greater proportion of women home office personnel and salaried employees than pr ojects in other i ndustry sectors. Firms that do industrial projects have lo wer percentages of women field employees. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%1 3 4 6 8 10 16 18 20 25 30 32 38 40 40 50 65 75 75 80 100 100 100 150 200 214 300 400 500Percent of Employees that are WomenTotal Number of Employees Proportion of Women Field Employees Linear (Proportion of Women Field Employees) Figure 4-11. Proportion of women field employees. 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%1 4 4 5 5 6 10 10 11 15 16 16 17 19 20 22 28 30 33 37 40 45 50 50 55 60 75 75 84 95 100 115 200 426Percent of Employees that are WomenTotal Number of Employees Proportion of Women Home Office Employees Linear (Proportion of Women Home Office Employees) Figure 4-12. Proportion of women hom e office and salaried employees.

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66 Employee Placement The second section of the surv ey identified the specific posit ions within the company in which women were employed. This section was divided into office positi ons, field supervisory positions, and trades positions. Office positions included receptionists, office managers, estimators, project engineers/assistant project managers, project ma nagers/department managers, vice presidents, presidents or CEOs, and other office positions. The women of the companies included in the survey were proportioned as follows: 52% were r eceptionists and office ma nagers and 48% were estimators, project engineers/assistant project managers, project managers/department managers, vice presidents, presidents or CEOs, and other office positions (Figure 4-13). Those positions categorized as “other” included accountants, interns, realtors, architects/engineers, chief financial officer, support personnel, human resources, I. T. personnel, marketing personnel, safety directors, construction ad ministrator, and director of new bus iness. A statistical analysis was performed and it was determined that there are greater opportunities (based on positions held by women) for women in home office positions in smaller firms (Kendall Correlation Test: Coef. = -0.207, = 0.009, N = 63). Field supervisory posit ions included supervisors, fo remen, field engineers/assistant supervisors, and other field posit ions. The women of the companies included in the survey were proportioned as follows: 63% foremen, 16% other fi eld positions, 15% fiel d engineers/assistant supervisors, and 6% supervisors (Figure 4-14). Those positions categorized as “other” included shop department supervisor, field clerk, project manager, safety coordinator, and journeyman.

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67 Receptionists 524 40% Office managers 163 12% Estimators 79 6% Project Engineers/Asst. Project Managers 243 18% Project Managers 138 11% Vice Presidents 31 2% Presidents 9 1% other office positions 127 10% Figure 4-13. Office positions of women. Supervisors 10 6% Formen 106 63% Field Engineers/Asst. Supervisors 26 15% Other field positions 27 16% Figure 4-14. Field positions of women.

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68 To determine the proportions of women in the trades, respondents were asked to indicate the percentage of women working in each trade on the company’s projects in the previous year. It should be noted that only 51 respondents answer ed this section. This may be because it is not common practice to keep a record indicating gend er of workers on the jobsite. Responses to question about the proportion of trades positions held by women ranged from 0% to 50%. Trades that were reported as having 0% women across the bo ard included roofers and sheet metal workers (Figure 4-15). Trades that aver aged less than 1% women included carpenters, concrete finishers, equipment operators, dr ywall installers and tapers, electricians, plumbers/pipelayers, structural iron and steel workers, and highway maintenance workers. Trades that averaged between 1% and 2% wo men included brick/block/stone masons, flooring installers and finishers, constr uction laborers, painters, constr uction helpers, construction and building inspectors, and other tr ades. Trades categorized as “other” included HVAC workers, landscapers, construction clean-up workers, and truck driver s. There were no trades that averaged over 2% women. The highest av erage percentages of women were found among construction and building inspec tors with 1.90% and constructi on laborers with 1.80%. These numbers are below the proportions of women in the trades repo rted by the Bureau of Labor Statistics (Figure 2-1).

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69 Figure 4-15. Proportions of women in trades on companies’ projects. The second part of the survey asked if and how gender is considered when assigning work to new hires. Of the respondents, 16% reporte d that gender was a cons ideration when assigning work to new hires (Figure 4-16). These respond ents were then asked to describe how gender was considered in this process. Most consid erations were based on physical exertion that was expected from the workers. The follow ing were responses to this question:

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70 “In general, many laborer positions can requi re significant strength. Some women can't physically lift or haul some materials. Respectfully.” “If considering a trade position, it is more r easonable to hire men because the physicality of the work.” “Weight restraints of lifti ng and hoisting materials.” “Possibly easy-handling work w ould be assigned to women.” “Gender is considered because of the amount of physical/ma nual labor typically required, although, few women apply for these positions in the first place.” “Only ability to show up and work hard is considered. Also experience.” “Males are considered to be more suitable.” “They consider females not e fficient enough for field jobs.” “If it is a field position, are they qualified and can they physically handle it. If it is an office or supervisory position can they handle it emotionally?” “We are based on meritocracy. The position has minimum qualifications. Sex, race, religion, etc is not an issue we are an EEO company.” “Women are considered an advantage.” Yes 9 16% No 47 84% Figure 4-16. Gender is a c onsideration when assigning work to new hires.

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71 Employee Recruitment The objective of the third pa rt of the survey was to de termine if the respondents’ companies had any specialized recruitment program s or efforts in place for the hiring of women or if they had any particular recruitment pr actices against the hiri ng of women. Of the respondents, 86% reported that th eir company did not have any policies against the hiring of women, 12% had no information on whether or not their company had such policies, and 2% reported that their companies did have policies, either written or verbal against the hiring of women (Figure 4-17). Yes 2 2% No 83 86% No Information 12 12% Figure 4-17. Company has polic ies against hiring women. Information was also sought on whether or not the respondent’s company had a program that was meant to specifically target women fo r employment. Of the respondents, 76% reported that they did not have a program to specifically target women, 19% respon ded that they did not have any information in order to answer this question, and 5% responded that they did indeed have a program to target wome n for employment (Figure 4-18). Respondents who stated that their firms had programs to target women were asked to elaborate on or to describe those

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72 programs. The resultant descriptio ns indicated that some of thes e firms did not actually have specific programs that targeted women. The fo llowing list contains th e responses that were received when the respondent was asked to give a short summary of the recruitment program for women: “MBE Requirements” “We have an EEO statement but we hire w hoever is qualified, has the best employment references and tests the best on the equipmen t. We don’t target any race or sex but the quality of workmanship.” “We choose the best candidate no matter race or gender” “Affirmative Action Plan to identify qualified applicants th rough outreach and colleges.” “Typically, a certain percenta ge of work on government contracts is supposed to be subbed out to minority and/or women-owned bus inesses. These are the only guidelines we have on this...” “We do most of our recruiting at UF. All appl icants are interviewed and considered on a level playing field regardless of gender. Fo r the past 3 years, our summer internships have been equally split between males and females, based on qualifications.” Yes 5 5%No 74 76%No Information 18 19% Figure 4-18. Company has a program to target women for employment.

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73 A statistical analysis was performed to de termine if there was a correlation between companies that reported having a recruitment program to specifically target women and the percentages of women field employees and home o ffice personnel and salaried employees. Both the Pearson and Kendall Correlation Tests showed that no variables had a significant correlation. Reported recruitment efforts are not relate d to the percentage of women employees. Skill Productivity Observations The fourth section of the survey questionnair e was designed to record the observations of how well women performed on workrelated skills and tasks when compared to male counterparts. The tasks and skills tested in this section were deve loped from the literature review. Respondents were asked to rate the level of performan ce of women when compared to men. To numerically quantify th e data collected, responses were converted as follows: “women perform much worse” = “-3”, “women perform wo rse” = “-2”, “women perform slightly worse” = “-1”, “women perform equal to men” = “0”, “w omen perform slightly better” = “1”, “women perform better” = “2”, “women perform much be tter” = “3”. To analyze the data collected, respondents were grouped based upo n their gender, whether a stude nt or industry professional, and whether experienced in construction or not. When all responses were analyzed, an initial analysis showed that respondents thought that women perform slightly better at tasks involving communication sk ills, with an average ranking of 0.736, and sensitivity to the emotions of othe rs, with an average ranking of 1.241 (Figure 419). The initial analysis also showed that the respondents thought that women performed worse than men in tasks involving physical streng th, with an average ranking of -1.595. The differences between men and women for the rati ngs on other skill/task performances were not appreciable.

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74 Manual Dexterity, 0.253 Physical Strength, 1.595 Spatial Perception, 0.085 Leadership, 0.069 Group Interaction and Teamwork, 0.395 Supervision of other workers, 0.058 Communication, 0.736 Sensitivity to the emotions of others, 1.241 Computer Literacy, 0.205 Mathematical Calculations, 0.108 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal to Men Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 4-19. Observations from industry prof essionals and student re spondents on skill/task performance. When responses from industry professionals we re grouped together, an initial analysis of their responses revealed that th eir perception was that women pe rform slightly better at tasks involving communication skills, with an average ranking of 0.900, and sensitivity to the emotions of others, with an av erage ranking of 1.172 (Figure 4-20). They also ranked women as performing “equal to men” to “sli ghtly better” on tasks involving computer literacy skills, with an average ranking of 0.500. The initial analysis also showed that thes e respondents thought that women performed between “slightly worse” and “w orse” than men in tasks involving physical strength, with an average ranking of -1.481. The responses from the industry professionals that were men were grouped together for a separate analysis. An initial analysis of their responses showed that th ey perceive that women perform slightly better at tasks involving communication skills, with an average ranking of 1.000 and equal to men in tasks involvi ng spatial perception and supervision of other workers (Figure

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75 4-21). They also ranked wome n between performing “slightly be tter” and “better” on tasks involving sensitivity to the emotions of others with an average ranking of 1.455. The initial analysis also showed that these respondents t hought that women performed worse than men in tasks involving physical strength, with an average ranking of -1.833. Manual Dexterity, 0.222 Physical Strength, 1.481 Spatial Perception, 0.038 Leadership, 0.034 Group Interaction and Teamwork, 0.310 Supervision of other workers, 0.103 Communication, 0.900 Sensitivity to the emotions of others, 1.172 Computer Literacy, 0.500 Mathematical Calculations, 0.115 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal toMen Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 4-20. Observations from industry profes sional respondents on sk ill/task performance. Manual Dexterity, 0.083 Physical Strength, 1.833 Spatial Perception, 0.000 Leadership, 0.167 Group Interaction and Teamwork, 0.273Supervision of other workers, 0.000Communication, 1.000 Sensitivity to the emotions of others, 1.455 Computer Literacy, 0.417 Mathematical Calculations, 0.200 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000 Women Perform Much Worse WomenPerform WorseWomen Perform Slightly Worse Women Perform Equal toMen Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 4-21. Observations from men industry pr ofessional respondents on sk ill/task performance.

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76 When responses from industry professionals th at were women were grouped together, the analysis of their responses showed that they per ceive that women perform slightly better at tasks involving communication skills, with an average ranking of 0.833, and sensitivity to the emotions of others, with an av erage ranking of 1.000 (Figure 4-22). They also ranked women as performing between “equal to men” and “slightly better” on tasks involv ing computer literacy skills, with an average ranking of 0.556. The initial analysis also showed that these respondents thought that women performed slightly worse than men in tasks involving physical strength, with an average ranking of -1.200. Next, student responses were grouped together and an initia l analysis was performed. Responses of all students showed that they percei ved that women perform slightly better at tasks involving sensitivity to the emotions of others, with an average ranking of 1.276 (Figure 4-23). They also ranked women as performing between “equal to men” and “slightly better” on tasks involving communication skills, with an average ranking of 0.649, and group interaction/teamwork, with an average of 0.439. This analysis also showed that these respondents thought that women performed between “slightly worse” and “worse” than men in tasks involving physical strength, with an average ranking of -1.649. When responses of male students were grouped together, the analysis of their responses showed that they perceived women as performing slightly better at task s involving sensitivity to the emotions of others, with an average ra nking of 1.073 (Figure 4-24) They also ranked women as performing between “equal to men” and “slightly better” on tasks involving communication, with an average ranking of 0.450. Th e initial analysis also showed that these respondents thought that women performed worse th an men in tasks involving physical strength,

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77 with an average ranking of 1.700, and performing between “equal to men” and “slightly worse” on tasks involving manual dexterity, w ith an average ranking of -0.425. Manual Dexterity, 0.333 Physical Strength, 1.200 Spatial Perception, 0.063 Leadership, 0.176 Group Interaction and Teamwork, 0.333 Supervision of other workers, 0.167 Communication, 0.833 Sensitivity to the emotions of others, 1.000 Computer Literacy, 0.556 Mathematical Calculations, 0.063 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal toMen Women Perform Slightly Better Women Perform Better Women PerformMuch Better Figure 4-22. Observations from women industr y professional respond ents on skill/task performance. Manual Dexterity, 0.268 Physical Strength, 1.649 Spatial Perception, 0.107 Leadership, 0.086 Group Interaction and Teamwork, 0.439 Supervision of other workers, 0.035 Communication, 0.649 Sensitivity to the emotions of others, 1.276Computer Literacy, 0.052 Mathematical Calculations, 0.105 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000 Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal toMen Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 4-23. Observations from student respondents on skill/task performance.

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78 Manual Dexterity, 0.425 Physical Strength, 1.700 Spatial Perception, 0.079 Leadership, 0.050 Group Interaction and Teamwork, 0.282 Supervision of other workers, 0.125 Communication, 0.450 Sensitivity to the emotions of others, 1.073 Computer Literacy, 0.025 Mathematical Calculations, 0.256 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal to Men Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 4-24. Observations from men stude nt respondents on skill/task performance. When responses of women stude nts were grouped together, the analysis of their responses showed that they perceived women as performing better at tasks involving sensitivity to the emotions of others, with an av erage ranking of 1.756 (Figure 4-25). They also ranked women as performing “slightly better” on tasks involving communication, with an average ranking of 1.118, and tasks involving group interaction and t eamwork, with an average ranking of 0.778. They also ranked women as performing between “equal to men” and “slightly better” on tasks involving spatial perception, with an average ranking of 0.500, tasks supervision of other workers, with an average ranking of 0.412, and task s involving leadership skills, with an average ranking of 0.389. The analysis also showed th at these respondents thought that women performed worse than men in tasks involving phys ical strength, with an average ranking of 1.529.

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79 Respondents with construction work experience, including both industr y professionals and those students which have worked in construc tion, observed that women performed slightly better than men on tasks involving sensitivity to th e emotions of others, w ith an average ranking of 1.254, and tasks involving communication skill s, with an average ranking of 0.745 (Figure 426). The analysis also showed that these res pondents thought that women performed worse than men in tasks involving physical strengt h, with an average ranking of -1.651. Respondents without construction work experien ce, which included students which had not worked in the construction industry, perceived th at women performed slightly better than men on tasks involving sensitivity to the emotions of others, with an average ranking of 1.211, and tasks involving communication skills, wi th an average ranking of 0.757 (F igure 4-27). The analysis also showed that these responde nts thought that women performed slightly worse than men in tasks involving physical strength, with an average ranking of -1.400. Manual Dexterity, 0.125 Physical Strength, 1.529 Spatial Perception, 0.500 Leadership, 0.389 Group Interaction and Teamwork, 0.778 Supervision of other workers, 0.412 Communication, 1.118 Sensitivity to the emotions of others, 1.765 Computer Literacy, 0.111 Mathematical Calculations, 0.222 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal to Men Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 4-25. Observations from women stude nt respondents on skill/task performance.

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80 Manual Dexterity, 0.302 Physical Strength, 1.651 Spatial Perception, 0.000 Leadership, 0.030 Group Interaction and Teamwork, 0.400 Supervision of other workers, 0.000 Communication, 0.746 Sensitivity to the emotions of others, 1.254 Computer Literacy, 0.294 Mathematical Calculations, 0.111 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal toMen Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 4-26. Observations from respondents wi th construction work experience on skill/task performance. Manual Dexterity, 0.105 Physical Strength, 1.400 Spatial Perception, 0.300 Leadership, 0.400 Group Interaction and Teamwork, 0.400 Supervision of other workers, 0.263 Communication, 0.737 Sensitivity to the emotions of others, 1.211 Computer Literacy, 0.105 Mathematical Calculations, 0.105 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal toMen Women PerformSlightly Better Women Perform Better Women Perform Much Better Figure 4-27. Observations from respondents with no construction work experience on skill/task performance.

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81 When these groupings of respondents were compar ed to each other based on the associated tasks, there were few differences in the respons e patterns. In tasks i nvolving manual dexterity, women students perceived women’s performance differently from other groups, i.e., women students felt that women perfor med better on tasks involving ma nual dexterity (Figure 4-28). This also differs from the perceptions of women industry professionals. In tasks involving physic al strength, all groups appear to ag ree that to some extent women perform worse than men (Figure 4-29). Opinions in areas of spatial perception tasks of women are much more varied, but still fall within the range of equal performance as compared to male counterparts (Figure 4-30). Per ceptions of leadership skills also vary, but still fall within the range of equal performance (Figure 4-31). In tasks involving group in teraction and teamwork, all groups appear to agree that women perform e qual to slightly better than men, with female students tending more toward “slightly better” (F igure 4-32). Except for the men students, all respondent groupings perceived that women performed equally to men to slightly better in tasks involving the supervision of othe r workers (Figure 4-33). In tasks involving communication skills, all groups appear to agre e that to some extent women perform better than men (Figure 434). All groups also appear to agree that women perform “slightly better” to “better” than men on tasks involving sensitivity to the emotions of others (Figure 4-35). Pe rceptions of computer literacy skills vary, but still fall within the rang e of equal performance (F igure 4-36). All groups tend more toward better performance from wome n, with the exception of those respondents with no work experience related to c onstruction. In tasks involving mathematical calculations, it appears that most groups percei ve that to some degree women perform worse, although all averages still fall within the equal performan ce range (Figure 4-37). Women students however,

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82 tend to disagree with other groups and believe that women are to some degree better at mathematical calculations. Figure 4-28. Manual dexterit y, average rankings by group. Figure 4-29. Physical stre ngth, average rankings by group.

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83 Figure 4-30. Spatial percep tion, average rankings by group. Figure 4-31. Leadership sk ills, average rankings by group.

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84 Figure 4-32. Group interaction/t eamwork, average rankings by group. Figure 4-33. Supervision of other workers, average rankings by group.

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85 Figure 4-34. Communicati on, average rankings by group. Figure 4-35. Sensitivity to the emoti ons of others, average rankings by group.

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86 Figure 4-36. Computer liter acy, average rankings by group. Figure 4-37. Mathematical calcul ations, average rankings by group.

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87 A statistical analysis was perf ormed, to further the understandi ng of trends in response to skill/task performance of wome n. The following results were found to be statistically significant: Construction industry profe ssionals rated women higher in tasks involving computer literacy skills than student respondent s (Pearson Correlati on Test: Coef. = 0.241, = 0.012, N = 88; Kendall Correlation Test: Coef. = 0.242, = 0.008, N = 88). Women respondents rated women higher in areas of physical strength than the male respondents (Pearson Corre lation Test: Coef. = 0.228, = 0.018, N = 84; Kendall Correlation Test: Coef. = 0.197, = 0.029, N = 84). Women respondents rated women higher in ta sks involving spatial perception than the male respondents (Pearson Co rrelation Test: Coef. = 0.212, = 0.028, N = 82; Kendall Correlation Test: Coef. = 0.185, = 0.039, N = 82). Women respondents rated women higher in ta sks involving leadership skills than the male respondents (Pearson Co rrelation Test: Coef. = 0.202, = 0.03, N = 87; Kendall Correlation Test: Coef. = 0.169, = 0.048, N = 87). Women respondents rated women higher in task s involving supervision of other workers than the male respondents (Pearson Correlation Test: Coef. = 0.221, = 0.021, N = 86; Kendall Correlation Test: Coef. = 0.209, = 0.021, N = 86). Women respondents rated women higher in ta sks involving mathematical calculations than the male respondents (Pearson Correlation Test: Coef. = 0.242, = 0.014, N = 83; Kendall Correlation Test: Coef. = 0.241, = 0.012, N = 83). Women respondents rated women higher in tasks involving communication skills than the male respondents (Pearson Correlation Test: Coef. = 0.176, = 0.051, N =87; Kendall Correlation Test: Coef. = 0.165, = 0.048, N = 87). Student respondents with no construction work experience rated women higher in tasks involving physical strength than the students with construction work experience (Pearson Correlation Test: Coef. = 0.248, = 0.031, N = 57; Kendall Correlation Test: Coef. = 0.259, = 0.021, N = 57). Student respondents with no construction work experience rated women higher in tasks involving leadership than the students w ith construction work experience (Pearson Correlation Test: Coef. = 0.239, = 0.035, N = 58; Kendall Correlation Test: Coef. = 0.187, = 0.066, N = 58).

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88 The survey was designed to coll ect additional information on situ ations that relate to the skills and tasks studied, such as complaints of musculoskeleta l injuries or pains by women, whether companies purchase and supply PPE sp ecially made for women, observations of women’s interaction in peer gr oups, and productivity observations. This part of the survey questionnaire asked for both quantita tive and qualitative answers. Respondents were asked to indi cate whether or not they found that female employees expressed more concern about musculoskeletal inju ries or pains than male employees. Of the respondents, 44% reported that they did not find that women expressed more concern, 37% reported that they did not have information in order to provide an info rmed answer to this question, and 19% reported that they did find that women expressed more concern about musculoskeletal injuries or pains than male employees (Figure 4-38). Yes 17 19% No 39 44% No Opinion 32 37% Figure 4-38. Female employees express more concern about musculoskeletal injuries. Respondents were then asked if their compa ny purchased and supplied Personal Protection Equipment (PPE) that was specially made to fit women. Of the respondents, 47% reported that

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89 they did not supply PPE that was made specially for women, 37% reported th at they did not have information in order to make an informed answ er to this question, 9% reported that they did supply PPE that was specially made to fit women, and 7% reported that PPE specially made to fit women was not commercially available fo r purchase by the company (Figure 4-39). Yes 8 9% No 41 47% Specialized PPE is not commercially available 6 7% No Opinion 33 37% Figure 4-39. Company supplie s PPE especially for women. Information was also sought on respondent observations of how well women interact in peer groups at work. The following responses showed positive inte raction differences: “I think women interact better than men in peer groups. Their communication skills are usually better.” “In my observations women interacted well wi th peer groups. They would take charge and/or do what was asked with no bitching or failure.” “Interaction is/was great. Very outgoing.” “Women communicate well and express any expectations from coworkers.” “They are more friendly and co me up with better ideas.”

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90 “Women seem to interact in peer groups ra ther well because a lot of the time they are good listeners and they also take actions to get the work done.” “They tend to have better communication skills so I think they interact better and can explain their ideas better.” “They interact really well. They have th e required knowledge of th e topic and also they can take part in all gr oup discussions properly.” “They are very well con cerned about others.” “Talkative and out-going.” “Women tend to listen more and engage othe rs in dialogue versus directed actions” “Take leadership Interact well if knowledge is there Aggressive when needed” The following responses displayed a negative interaction difference: “Women are treated like peers as long as they do not isolate themselves and demand special treatment. If they can do the work like the guys and know they're stuff, there's never a problem.” “Emotions play a larger role” “I find it difficult to work with women because few get to the point of the discussion and are not as straight forward as most men. Ha rd to trust women as much which can make group work difficult.” “Women are more defensive and less trusting of other female peers due to competition.” Other responses included those that displayed a gender-based interaction difference, but the connotation could not be determined; those that displayed a neutra l or equal observation about interaction in peer groups and thus differences could not be determined; and those that displayed that the respondent had no basis for an opinion. These response s are included in Table E-1. Information was also sought on respondent obs ervations of any differences in productivity between male and female employees. The following responses displayed positive feedback toward women’s productivity:

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91 “Female probably more productive. Men have other men to converse with (i.e. slack more often)” “Seem to be the same. Men might be a little less productive by letting attitudes get in the way.” “Women focus well even when tackling multiple tasks.” “Female employees are more productive and wo rk the entire day. Males tend to play computer games and distract themselves.” “In the construction office, the female employ ees seem more task-oriented and maintain focus.” “Observations are in PE, APM, PM, Estim ating employee groups. Females are often more productive than male counterparts.” “Women tend to be more organized ther efore they are often more productive.” “Women tend to multi-task more and are succe ssful in positions that require management of multiple deadlines at one time.” “A running joke in our company is that al l the women who have taken the LEED exam pass the first time, all the men the second. Not sure what this is about... maybe the women just take it more serious ly, maybe they catch on faster....” “Females tend to respond quicker with a completed task than males.” The following responses displayed negativ e feedback toward women employee’s productivity: “I think in terms of manual labor, men may be slightly more productive than women for physical/anatomical reasons.” “Only some physical limitations.” “Women may let emotion interfere with productivity.” “The only main reason in difference for men vs women is that normally men are better in the strength field so sometimes men can be faster when it involves strength to get something done fast.” “I think they lack physical st rength and they have more fam ily issues and family bindings than men.” “Men work faster with greater stamina!”

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92 “Female employees get more physically tired from manual labor than male employees which impacts productivity.” “Most of our female employees smoke, many smoke breaks during the day.” Other responses included those that displayed that there wa s no difference between male and female employee’s productivity at work; thos e that displayed situa tional connotations in their answers; and those that di splayed that the respondent did not have information in order to make a comparison of productivity. Thes e responses are included in Table E-2. Personality Trait Observations The fifth portion of the survey was designed to obtain information on the degree to which personality traits are portrayed in employees. The personality traits us ed were based on those examined in the literature review. The persona lity traits were ranked by on a Likert-type scale as follows: “only describes men” = “-3”, “more descriptive of men” = “-2”, “slightly more descriptive of men” = “-1”, “there is no differen ce” = “0”, “slightly more descriptive of women” = “1”, “more descriptive of women” = “2”, “only describes women” = “3”. To analyze the data collected, respondents were gr ouped by gender, whether they are a student or industry professional, and whether they are experienced in construction or have no work experience related to construction. The analysis showed that ther e was a general consistency fr om all groups that to some degree men were more assertive than women (F igure 4-40). The average response of almost every group still tended toward “there is no diffe rence”, with the exception of male students, with an average of -0.590, and students as a whol e, with an average response of -0.527. These two groups are tending more toward assertiveness bei ng “slightly more de scriptive of men”. Those respondents with no construction experi ence fell half way between “there is no difference” and “slightly more descriptive of me n”, with an average ranking of -0.500. Women

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93 as a whole and industry professiona ls appear slightly less apt to think of men as more assertive than women than other groups. Figure 4-40. Assertiveness, average rankings by group. All groups also appear to agree that to some extent men have higher self esteem than women (Figure 4-41). The average response of industry professionals and student respondents tended toward “there is no difference”, with an average of -0.356. Those respondents not experienced in construction work (-0.550) and women students (-0.688) appear to go against the trend and tend toward “slightly mo re descriptive of men”. Male industry professionals appear slightly less apt to think of me n as having higher self-esteem than other groups, with an average response of -0.222.

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94 Figure 4-41. High self-est eem, average rankings by group. There was a general consistency among all gr oups that to some degree women were more extroverted than men, with the exception of male students and respondents with no construction work experience (Figure 4-42). The average re sponse of industry professionals and student respondents tended toward “there is no difference”, with very little variati on in the averages of all group responses. The greatest differences ar e seen between averag e responses of women students, with an average of 0.267, and men stude nts and respondents with no construction work experience; both groups having an average response of 0.000. Wo men students appear slightly more apt to think of women as more ex troverted than men than other groups.

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95 Figure 4-42. Extroversion, average rankings by group. All groups appear to agree that to some extent women are more anxious, with the exception of men industry professionals (Figur e 4-43). The greatest differences are seen between average responses of women students and men industry profes sionals. Men industry professionals, with an average response of 0.000, a ppear to state that “there is no difference”, while women students, with an average of 0.867, ar e tending more toward a response of “slightly more descriptive of women”. Those respondents with no construction work experience also appear more apt to think of women as more anxious (0.70) than other groups. There was a general consistency from all gr oups that to some degree women were more creative than men (Figure 4-44). The average response of indus try professionals and student respondents, however, still tended toward “there is no difference”. Women as a whole and industry professionals appear slightly more apt to think of women as more creative than men than other groups.

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96 Figure 4-43. Anxiety, average rankings by group. Figure 4-44. Creative/idea gene rating, average rankings by group. There was also general consistency from all gr oups that to some degree women were more stressed than men (Figure 4-45). The average response of industry professionals and student

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97 respondents tended toward “there is no difference”, with very little variati on in the averages of all group responses. The greatest difference was seen between the aver age response of women students of 0.563, and all of the other groups. Wo men students appear slightly more apt to think of women as being more stressed than men. All groups appear to agree that to some extent women are more trusting, with the exception of men industry professionals (Figur e 4-46). The greatest differences are seen between the average responses of women as a whole, those respondents with no construction work experience (0.40), and men in dustry professionals (0.00). Me n industry professionals, with an average response of 0.000, appear to state that “there is no difference”, while women students, with an average of 0.500, are half way between responses of “there is no difference” and “slightly more descriptive of women”. Figure 4-45. Stress, av erage rankings by group.

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98 Figure 4-46. Trust, average rankings by group. In reference to the personality trait of aggression, all groups a ppear to agree that to some extent men are more aggressive (Figure 4-47). The greatest differences are seen between the average responses of men student s and industry professionals. I ndustry professionals, with an average response of -0.429, tend more toward the opinion that “there is no difference”, while men students, with an average of -1.026, tend toward a response of “slightly more descriptive of men”. The average of industry professionals a nd student respondents al so tends toward men being slightly more a ggressive than women. There was general consistency from all groups that to some degree women were more tender-minded than men (Figure 4-48). The av erage response of industry professionals and student respondents tended towa rd “slightly more descriptiv e of women”. The greatest difference was seen between the average respons e of women students of 1.125, and men industry professionals, with an average of 0.250. Stude nts as a whole, women as a whole, and those

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99 respondents experienced in construction work app ear slightly more apt to think of women as more tender-minded than other groups. Figure 4-47. Aggression average rankings by group. Figure 4-48. Tender-mindedness, average rankings by group.

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100 There was also general consistency from all groups that to some degree men were more impulsive than women (Figure 4-49). The av erage response of indus try professionals and student respondents tended toward “there is no di fference”, with very little variation in the averages of all group responses. The greatest di fference was seen between the average response of respondents with no construction experience of -0.500, and all of the other groups. In reference to the personalit y trait of hard working, all gr oups appear to have slightly differing opinions, while still all tending toward no difference between men and women (Figure 4-50). The greatest differences ar e seen between the av erage responses of those who do not have construction work experience, with an average response of 0.100, and men industry professionals, with an average ranking of -0.111. Again, however, the differences in opinion are very slight. Figure 4-49. Impulsive, average rankings by group.

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101 Figure 4-50. Hard-working, average rankings by group. All groups appear to agree that to some extent women are more organized than men (Figure 4-51). All groups, w ith the exception of men students and men industry professionals, perceive women as “slightly” more organized than men. The greatest differences are seen between the average responses of women students, with an av erage response of 1.000, and men industry professionals, with an average response of 0.111. Men as a whole appear to state that “there is no difference” in the trait of organization. In reference to the personalit y trait of self-control, all gr oups, with the exception of men students and students as a whole, ap pear to agree that to some exte nt this trait is descriptive of women (Figure 4-52). While havi ng slightly differing opinions however, all groups are still tending toward no difference between men and wo men. The greatest differences are seen between the average responses of women students, with an av erage response of 0.188, and men students, with an average ranking of -0.073. Again, the differences in opinion are very slight.

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102 Figure 4-51. Organizati on, average rankings by group. Figure 4-52. Self-control, average rankings by group.

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103 In reference to the personalit y trait of dedication, all groups appear to have slightly differing opinions, while still all tending toward no difference between men and women (Figure 4-53). The greatest differences ar e seen between the av erage responses of those who do not have construction work experience, with an average response of -0.100, and women students, with an average ranking of 0.250. Figure 4-53. Dedication, average rankings by group. In summary, industry professionals and st udent respondents thought that women were slightly more tender-minded and organized when compared to men (Figure 4-54). Respondents also thought that men were slightly more a ggressive than women. There was little to no difference between men and women in personality traits of dedi cation, self-control, extroversion, and the trait of being hard-worki ng. While there was very little difference perceived between the average rankings of trust, stress, creativity, and anxiety, these traits tended more toward women’s personalities while impulsiveness, high self-esteem, and assertiveness tended more toward men’s personalities.

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104 Figure 4-54. Industry professi onals’ and students’ average ra nkings of personality traits. A statistical analysis was performed to better determine if there were trends in the responses based on categorized groups, percen tages of women employees, and degrees of personality traits of women. The following resu lts were found to be stat istically significant: As the percentage of women field employees in a company increas es, the perception of women’s high self-esteem increases (Pearson Correlation Test: Coef. = 0.263, = 0.036, N = 48; Kendall Correlation Test: Coef. = 0.214, = 0.04, N = 48). As the percentage of women home office pers onnel and salaried employees in a company increases, the perception of women’s cr eativity/idea generatio n increases (Pearson Correlation Test: Coef. = 0.381, = 0.002, N = 58; Kendall Correlation Test: Coef. = 0.255, = 0.008, N = 58). Construction industry professi onals rated women higher in the trait of creativity/idea generating than student respondents (Pearson Correlation Test: Coef. = 0.185, = 0.046, N = 84; Kendall Correlation Test: Coef. = 0.178, = 0.044, N = 84). Student respondents rated women higher in the trait of anxiet y than construction industry professionals (Pearson Correlation Test: Coef. = -0.144, = 0.095, N =84; Kendall Correlation Test: Coef. = -0.173, = 0.049, N = 84). Construction industry professi onals rated women higher in th e trait of aggression than student respondents (Pearson Co rrelation Test: Coef. = 0.271, = 0.007, N = 82; Kendall Correlation Test: Coef. = 0.242, = 0.009, N = 82).

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105 Women respondents rated women hi gher in the trait of creativity/idea generating than the male respondents (Pearson Co rrelation Test: Coef. = 0.259, = 0.009, N = 84; Kendall Correlation Test: Coef. = 0.187, = 0.036, N = 84). Women respondents rated women higher in th e trait of aggression than the male respondents (Pearson Corre lation Test: Coef. = 0.266, = 0.008, N = 82; Kendall Correlation Test: Coef. = 0.248, = 0.008, N = 82). Student respondents with no construction wo rk experience rated women higher in the trait of hard-working than the student re spondents with construction work experience (Pearson Correlation Test: Coef. = 0.256, = 0.027, N = 57; Kendall Correlation Test: Coef. = 0.289, = 0.014, N = 57). Statistical correlation tests were performed to determine if there were trends in answers between skill/task productivity obser vations of women and personality traits of women. Several correlations exhibited a tendency toward signif icance. Correlations between responses to skills/task productivity observations were noted in Tabl e D-2. Correlations between responses to personality traits of women are found in Table D-3. Significant correlations be tween skill/task productivity observations of wome n and personality traits of wo men are noted in Table D-4. Women in the Trades The final portion of the questionnaire deal t with the observations of women in the construction trades. This section asked the respondents to give their perceptions on the suitability of women in construction trades; name ly if they are more suited or less suited for some trades than others. Of the respondents, 47% reported that they did not find that women were more suited or less suited for some trades than others, 32% reported that they did find that women were more suited or less suited for some trades than others, and 21% reported that they had no basis on which to form an opinion on the s ubject (Figure 4-52). If the respondent did find a difference in their suitability, then they were asked to please explain. The following comments were made on the suitability of women in specific trades:

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106 “Better suited to more complicated work, elec trical work, carpentry, etc. Less suited to brute force type work like demolitio n, concrete cutting, laying block.” “I think in terms of management positions, th ey are better suited for upper management and project management versus manual labor or a superintendent posi tion, but their detail oriented nature makes them suitable for our industry.” “Women may struggle a bit more with high in tensity activities, for example concrete labor.” “I would argue that there is no specific task unless it was a shear strength-based trade. Even then, there is equipment that can be used to assist the female employee.” “Interior designers.” “In construction women would be very hard to place in some of the tradesdue to strength” “More suited for Interior Finish Trade type work” “manual labor” (assuming less-suited) “I feel that women are generally more orga nized and neat compared to some men. So, organizational tasks could be more suited for some women.” “Women cannot handle the highly physical positions such as block mason, drywall hangers, as well as men” “Less suited for some of the mo re physically demanding trades.” Other comments were found to be more general statements about gender differences rather than attributed to certain trades and are listed in Table E-3. Yes 27 32% No 39 47% No Basis for an opinion 18 21% Figure 4-52. Suitability in trades.

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107 CHAPTER 5 CONCLUSIONS When the ideas for this research began, th e construction industry was experiencing a severe skilled labor shortage a nd a thriving economy. Previous st udies were inconclusive as to whether the construction industry was actively se eking women in order to fill the gap in the trades. From this research it can be conclude d that the industry itself with the exception of specialized apprenticeship programs outlined in the li terature review, is not specifically targeting women with recruitment programs. While compan ies are not necessarily discriminating against women, they are also not looking to them as a potential skilled labor source. Most of the responding companies who did claim that they specifically targeted women for employment instead described their recrui tment program in terms of “f ollowing the laws” of equal opportunity employment or requirements set fort h for Minority Business Enterprises (MBEs). This could in part be due to the recent change s in economic status. For example, the current economy is laying-off employees rather than seeki ng out new sources of skilled labor. The fact still remains, however, that historically the cons truction industry does not invest in research and development, especially in areas of recruitment, as much as other industries. This is important because the economy will soon rebound and the cons truction industry finds itself with the same skilled labor shortage problem. A statistical analysis was performed to de termine if there was a correlation between companies that reported having a recruitment program to specifically target women and the percentages of women field employees and home o ffice personnel and salaried employees. Both the Pearson and Kendall Correlation Tests showed that no variables had a significant correlation. Recruitment efforts are not related to the percentage of women employed.

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108 In relationships between percentages of women employees and total numbers of employees, the study found that larger companie s have a greater proportion of female field employees. It should be clarifie d that women in the field might be employed in the field or the project office. This was not ascertained. The relationship be tween home office personnel and salaried employees had the opposite effect; as th e total number of home office personnel and salaried employees increases, the proportion of home office women employees decreases. The analysis also determined that there are greate r opportunities for women in home office positions in smaller firms, based on the positions of wome n within the companies that were studied. It should be noted here that this conclusion may be in fluenced by the nature of the respondents. Of all the surveys conducted, 62 respondents were men and 46 respondents were women. Of the industry professional respondents, 18 were men and 28 were women. This high proportion of women respondents indicates that there may be a bias among the respondents. This shows that women responding to the survey are those in ma nagement positions and automatically it is known that women are employed in those comp anies. The gender composition of survey respondents does not reflect the composition of the industry. From the gender composition of the responses, it may also be deduced that wome n have a greater propensity to participate in a study about women. This may mean that compan ies with fewer or no women in management positions were less likely to complete the surv ey. This may also influence the perceptions expressed about women in the survey. The analysis also found that subcontractor s have a smaller percen tage of women home office personnel and salaried employees. Als o, the greater the amount of work that is subcontracted, the greater th e proportion of women home office personnel and salaried employees. The relationships between the perc entage of women employees and the types of

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109 projects performed, it was found th at firms that do commercial proj ects have a greater proportion of women home office personnel and salaried empl oyees, and firms that do industrial projects have lower percentages of wome n field employees. Personal experience of the researcher and studies of labor statistics have shown similar results. Women with design backgrounds will also migrate to design-build positions. It may be the nature of the work or cultural influences of how genders should behave that influences the numbers of women working in certain fields. Cultural based gender stereotypes proclaim that appr opriate work for women is “cleaner” and less physically involved. This may be why fewer wome n are found in firms that self-perform large quantities of work; because these employees ar e closer proximity to physical/manual labor. Similarly, industrial projects may be viewed by so ciety as less feminine than commercial or other types of projects and t hus have fewer women. Of the respondents, 16% reported that gender was a consideration when assigning work to new hires. These respondents were then asked to describe how gender was considered in this process. Mostly, considerations were base d on the amount of physical exertion that was expected from the worker. This lends itself to the conclusion that most companies do not think about gender differences, and in times when it is, physical strength may be the only gender difference that the industry is c hoosing to recognize. As ment ioned previously, there was an overall sense in the responses to the survey that respondents were trying to somehow prove they were “following the law” rather than stating their perceptions of gender differences. Studies described in the lite rature review found that men and women perform differently on tasks. This difference can be attributed to a de gree to the genetic traits of their sex. When all responses to questions regardi ng women’s performance on typical tasks or skills related to construction work were analyzed, the results showed that respondents thought women perform

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110 slightly better at tasks involving communication sk ills and sensitivity to the emotions of others (Table 5-1). The analysis also showed th at the respondents thought that women performed worse than men in tasks involving physical strengt h. These aspects were al so found to be true in the gender studies described in th e literature (Figure 5-1). Prev ious gender studies, however, also found that men had advantages in group beha vior situations and co mputer literacy skills, and that women had advantages in leadershi p. In the current study, these skills were not perceived as tending toward a particular sex. Table 5-1. Advantages by gender in sk ills and tasks used in construction. Industry’s Responses Gender Study Findings Men: Physical Strength Women: Communication Sensitivity to the emotions of others Men: Physical Strength (Muscular Abilities) Group Interaction (Group Behavior) Computer literacy Women: Communication Sensitivity to the emotions of others (emotional intelligence) Leadership No Difference: Spatial Perception Manual Dexterity Mathematical Calculations Group Interaction Supervision of Other Workers Computer Literacy Leadership No Difference: Spatial Perception (Spatial and Mental Rotation) Manual Dexterity Mathematical Calculations Supervision of Other Workers

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111 Manual Dexterity, 0.253 Physical Strength, 1.595 Spatial Perception, 0.085 Leadership, 0.069 Group Interaction and Teamwork, 0.395 Supervision of other workers, 0.058 Communication, 0.736 Sensitivity to the emotions of others, 1.241 Computer Literacy, 0.205 Mathematical Calculations, 0.108 3.000 2.500 2.000 1.500 1.000 0.5000.0000.5001.0001.5002.0002.5003.000Women Perform Much Worse Women Perform Worse Women Perform Slightly Worse Women Perform Equal to Men Women Perform Slightly Better Women Perform Better Women Perform Much Better Figure 5-1. Findings of observa tions from industry profession als and student respondents on skill/task performance. In regards to observations of personality traits, industry professionals and student respondents thought that women were slightly more tender-minde d and organized as compared to men (Table 5-2). Respondents also thought th at men were slightly more aggressive than women. There was little to no difference betw een men and women in personality traits of dedication, self-control, extroversion, and the trai t of being hard-working. While there was very little difference seen between the average rankings of trust, stre ss, creativity, and anxiety, these traits still tended more toward women’s persona lities while impulsiveness, high self-esteem, and assertiveness still tended more toward men’s pe rsonalities. Gender stud ies analyzed in the literature review confirme d that men were more aggressive a nd assertive, and that women were Findings from survey agree with findings from literature review Findings from literature review that were not significant in survey Findings from survey that were not found in the literature review

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112 more tender-minded (Figure 5-2). The gender st udies analyzed, however, also found that women were higher in extraversion, anxiety, and trust, and that men were s lightly higher in self-esteem. Table 5-2. Tendencies by gende r of personality traits. Industry’s Responses Gender Study Findings Men: Aggressive Women: Tender-minded Organization Men: Aggressive Assertive High Self-esteem Women: Tender-minded Extroversion Anxiety Trust No Difference: Impulsiveness Creativity/Idea Generation Dedication Self-Control Extroversion Hard-Working Trust Stress Anxiety High Self-Esteem Assertive No Difference: Impulsiveness Creativity/Idea Generation (Ideas/Reflectiveness) Self-Control (Locus of Control) Organization (Orderliness) Not Studied: Dedication Hard-Working

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113 Figure 5-2. Findings of industry professionals’ and students’ aver age rankings of personality traits. Several explanations may be offered for the differences and similarities between the past gender study conclusions and the conclusions of this research on both skill/task performance ratings and degrees of personality traits. Since the differences th at were stated are similar to those found in the gender studies, it does not appear that the treatme nt of women in the construction industry is based on ge nder stereotypes. It was noted in this study that the industry respondents appeared somewhat timid to state that sexes are differen t; especially to state that any difference was more than slight. There is a possi bility that the industry is in a state of hypersensitivity to sexual discrimination. In other wo rds, instead of expressing the belief that everyone should be treated equal, as the law states, they ma y be attempting to perceive that genders are created equal or with identical tr aits. Another alternative explanation could be that the industry respondents perceive little difference between the se xes because minorities, in this Findings from survey agree with findings from literature review Findings from literature review that were not significant in survey Findings from survey that were not found in the literature review

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114 case women, involved in a group or a situation of ten alter their behavior to conform to their surroundings. There is also the possibility that women who choose construction as a career are of certain and distinct personality types; a different br eed that cannot be summed up with generalizations of women. Students and professionals differ in their perceptions of the tr aits of women. This stems from the lack of experience of students. Further studies on this topic need not be conducted with students. Recommendations to the constr uction industry begin by first th inking of gender differences as a positive advantage. If the industry can view differences positively and apply this knowledge, they may discover improvements in produc tivity and a more efficient workforce. The greatest areas of improvement that could come from considering gender differences may be in the recruitment of skilled workers. The i ndustry should understand the advantages of having women employees and the advantages to women of working in construction, to recruit skilled workers to fill job openings. Ov erall, the industry should invest in finding skilled labor sources. Recommendations to research ers begin by better understand ing the recruitment programs for women that are in-place and to identify thos e which are most successful. This may involve looking more closely at trades training programs, numbers of women in the trades, and how subcontractors and apprenticeships recruit workers. There should also be more research into why groups within the constructi on industry have differing opini ons on women’s performance of tasks and degrees of personality traits. This should also be compared against similar occupations. A further study could compare wome n who are in design-build firms to women in traditional design-bid-build firms in the commercial sector, to understand differences in the perceptions concerning women and also to examine reasons for th e career choices that women

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115 make. There should also be a survey conducted ex clusively of project managers. This survey should include questions on the number of women s upervised in the past. To make sure that there is clarity in the understanding of terms, the survey should also give definitions for the various skills and personality trai ts. There should also be further investigation into the industry’s seemingly hypersensitive toward gender differences and gender related issu es. More research should be conducted as to what impacts gender di fferences might have on construction work; for instance, since women are less aggressive than me n, does this mean they are safer on the jobsite than men? More extensive research should be conducted to determine how gender differences might improve the construction industry.

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116 APPENDIX A INSTITUTIONAL REVIEW BOARD SURVEY APPROVAL

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119 APPENDIX B SURVEY COVER LETTER

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120 APPENDIX C SURVEY

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124 APPENDIX D STATISTICAL CORRELATION TABLES Table D-1. Respondent demogr aphics correlation tests Correlation Finding Statement Test Coef. N Larger companies have a greate r proportion of female field employees. Pearson Kendall 0.391 0.205 0.001 0.018 57 57 As the total number of home office personnel and salaried employees increases, the propor tion of home office employee women decreases. Pearson Kendall -0.167 -0.088 0.086 0.149 68 68 Subcontractors have a smaller percentage of women home office personnel and salaried employees. Pearson Kendall -0.245 -0.192 0.020 0.027 71 71 The greater the amount of work that is subcontracted, the greater the proportion of wome n home office personnel and salaried employees. Pearson Kendall 0.244 0.075 0.024 0.201 66 66 Firms that do commercial projects have a greater proportion of women home office personnel and salaried employees. Pearson Kendall 0.235 0.192 0.024 0.027 71 71 Firms that do industrial projects have lower percentages of women field employees. Pearson Kendall -0.172 -0.185 0.098 0.056 58 58

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Table D-2. Correlation coefficients of skills/tasks. Physical Strength Spatial Perception Leadership Group Inte raction Supervision of Communication Sensitivity to the Compu ter Literacy Mathematical other workers Emotions of Others Calculations Correlation Test Pearson Kendall Pearson Kendall Pearson Kendall Pearson Kendall Pearson Kendall Pearson Ke ndall Pearson Kendall Pearson Kendall Pearson Kendall Manual Coef. .194* 0.057 -0.035 -0.037 .270** .194* 0.072 0.021 .207* 0.141 0.077 0.082 0.08 0.118 -0.132 -0.078 0.151 0.066 dexterity r 0.039 0.277 0.382 0.358 0.007 0.022 0.261 0.412 0.031 0.074 0.246 0.193 0.236 0.106 0.118 0.21 0.091 0.256 N 83 83 78 78 82 82 81 81 82 82 82 82 82 82 82 82 80 80 Physical Coef. 1 1 0.176 0.165 .378** .337** .183* 0.156 0.172 0.075 -0.055 -0.057 -.211* -.211* -0.024 -0.028 0.107 0.038 Strength r 0.06 0.051 0 0 0.05 0.055 0.062 0.223 0.312 0.277 0.029 0.014 0.415 0.387 0.17 0.354 N 84 84 79 79 83 83 82 82 82 82 82 82 82 82 83 83 81 81 Spatial Coef. 0.176 0.165 1 1 .221* 0.112 .249* .190* .274** 0.159 .211* 0.136 0.129 0.113 0.09 0.065 .365** .266** Perception r 0.06 0.051 0.023 0.129 0.012 0.027 0.007 0.056 0.03 0.082 0.125 0.124 0.213 0.257 0 0.005 N 79 79 82 82 82 82 81 81 81 81 80 80 81 81 81 81 79 79 Leadership Coef. .378** .337** .221* 0.112 1 1 .574** .518** .506** .335** .245* .184* -0.03 0 0.129 0.025 .329** .209* r 0 0 0.023 0.129 0 0 0 0 0.012 0.025 0.394 0.498 0.119 0.399 0.001 0.019 N 83 83 82 82 87 87 85 85 85 85 85 85 85 85 86 86 82 82 Group Coef. .183* 0.156 .249* .190* .574** .518** 1 1 .368** .276** .246* .272** 0.17 .275** 0.146 0.058 .231* .214* Interaction r 0.05 0.055 0.012 0.027 0 0 0 0.002 0.012 0.002 0.06 0.002 0.091 0.273 0.019 0.015 N 82 82 81 81 85 85 86 86 85 85 84 84 85 85 85 85 82 82 Supervision of Coef. 0.172 0.075 .274** 0.159 .506** .335** .368** .276** 1 1 .303** .261** .274** .251** .351** .341** .298** .209* other workers r 0.062 0.223 0.007 0.056 0 0 0 0.002 0.002 0.003 0.005 0.004 0 0 0.003 0.019 N 82 82 81 81 85 85 85 85 86 86 85 85 86 86 85 85 82 82 Communication Coef. -0.055 -0.057 .211* 0.136 .245* .184* .246* .272** .303** .261** 1 1 .582** .519** 0.161 0.117 0.153 0.12 r 0.312 0.277 0.03 0.082 0.012 0.025 0.012 0.002 0.002 0.003 0 0 0.069 0.104 0.086 0.11 N 82 82 80 80 85 85 84 84 85 85 87 87 86 86 86 86 81 81 Sensitivity to Coef. -.211* -.211* 0.129 0.113 -0.03 0 0.17 .275** .274** .251** .582** .519** 1 1 0.171 0.139 0.074 0.094 the Emotions r 0.029 0.014 0.125 0.124 0.394 0.498 0.06 0.002 0.005 0.004 0 0 0.058 0.07 0.255 0.169 of Others N 82 82 81 81 85 85 85 85 86 86 86 86 87 87 86 86 82 82 Computer Coef. -0.024 -0.028 0.09 0.065 0.129 0.025 0.146 0.058 .351** .341** 0.161 0.117 0.171 0.139 1 1 .352** .245** Literacy r 0.415 0.387 0.213 0.257 0.119 0.399 0.091 0.273 0 0 0.069 0.104 0.058 0.07 0.001 0.007 N 83 83 81 81 86 86 85 85 85 85 86 86 86 86 88 88 83 83 **. Correlation is significant at the 0.01 level (1 tailed). *. Correlation is significant at the 0.05 level (1 tailed).

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Table D-3. Correlation coeffici ents of personality traits. Pearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson KendallAssertiveness Coef..234* .244** 0.019-0.073-.193* -.221* -.233* -.221* 0.169.161* -0.166-0.157.36 2** .403** -.359** -.395** 0.0060.0240.0420.07-0.136-.162* -0.165-0.161-0.141-0.126 r 0.0170.0080.4310.2330.0420.0140.0180.0130.0630.0490.0690.056000.00100.4790.4030.3520.2480.110.050.0680.0530.1030.108 N 8383828281818282838382828080808083838383838383838383 High Self Coef.11.225* 0.139-.305** -.322** -.300** -.209* -0.077-0.065-.266** -.204* 0.0810.145-.255* -.289** .205* .167* -.259** -0.13-.473** -.429** -.375** -.259** -0.162-0.117 Esteem r 0.020.0840.0020.0010.0030.0190.2440.2570.0070.020.2350.0730.010.0020.030.0450.0080.1150000.0050.0 690.126 N 8585848483838383848484848181828285858585858585858585 ExtroversionCoef..225* 0.13911.240* .275** -0.0460.003-0.0320.041-0.040.005-0.139-0.0670.0330.07.295** .200* 0.0630.074-0.0490.002-.430** -.324** -0.171-0.02 r 0.020.084 0.0140.0030.340.4890.3890.3390.360.4810.1080.2520.3850.2450.0030.0210.2850.2370.3280.490 0.0010.060.423 N 8484848483838383838383838181818184848484848484848484 Anxiety Coef.-.305** -.322** .240* .275** 11.250* 0.155.38 1** 330** 0.1250.101-0.044-0.112.443** .422** 0.0560.0660.169.179* .287** .306** -0.139-0.153-0.0310.043 r 0.0020.0010.0140.003 0.0110.06000.1280.1530.3470.128000.3050.2490.0620.0420.0040.0010.1040.0620.38 90.336 N 8383838384848383838384848282828284848484848484848484 Creativity/IdeaCoef.-.300** -.209* -0.0460.003.250* 0.15511.362** .288** .496** .443** -0.055-0.123.207* 0.148-.235* -.165* .211* .186* .469** .415** .289** 0.153.492** .419** Generation r 0.0030.0190.340.4890.0110.06 00.002000.3110.1040.0320.070.0160.0450.0270.035000.0040.06100 N 8383838383838484848483838282818184848484848484848484 Stress Coef.-0.077-0.065-0.0320.041.381** 330** .362** .288** 110.178.197* 0.0420.0220.1710.114-0.145-0.023-0.080.0010.0990.112-0.051-0.054.186* .16 7* r 0.2440.2570.3890.3390000.002 0.0520.0210.3550.4080.0620.1240.0930.4060.2320.4970.1810.1220.3230.289 0.0440.047 N 8484838383838484868684848282828285858686868685858585 Trust Coef.-.266** -.204* -0.040.0050.1250.101.496** .443** 0.178.197* 11-0.064-0.084.242* .187* 0.0320.0340.010.0080.1620.139.207* 0.14.405** .370** r 0.0070.020.360.4810.1280.153000.0520.021 0.2850.1930.0140.0280.3840.360.4630.470.070.0750.0290.0750 0 N 8484838384848383848485858282838385858585858585858585 Aggression Coef.0.0810.145-0.139-0.067-0.044-0.112-0.055-0.1230.0420.022-0.064-0.08411-0.114-.310** 0.110.1390.140.11-0.169 -.225* 0.037-0.0760.0420.053 r 0.2350.0730.1080.2520.3470.1280.3110.1040.3550.4080.2850.193 0.1570.0010.1620.0750.1050.1410.0640.0 10.3720.2190.3530.3 N 8181818182828282828282828282808082828282828282828282 Tender-Coef.-.255* -.289** 0.0330.07.443** .422** .207* 0.1480.1710.114.242* .187* -0.114-.310** 110.032-0.04-0.15-0.12.302** .399** 0.155.233** 0.1520.135 mindedness r 0.010.0020.3850.245000.0320.070.0620.1240.0140.0280.1570.001 0.3870.3390.0880.1190.00300.0810.0090 .0850.092 N 8282818182828181828283838080838383838383838383838383 Impulsiveness Coef..205* .167* .295** .200* 0.0560.066-.235* -.165* -0.145-0.0230.0320.0340.110.1390 .032-0.04110.0020.015-.208* -0.131-.179* -0.139-0.058-0.052 r 0.030.0450.0030.0210.3050.2490.0160.0450.0930.4060.3840.360.1620.0750.3870.339 0.4910.440.0280.0850 .050.0750.2990.297 N 8585848484848484858585858282838386868686868686868686 Hard WorkingCoef.-.259** -0.1250.0630.0740.169.179* .2 11* .186* -0.080.0010.010.0080.140.11-0.15-0.1210.0020.01511. 246* .170* .292** .185* .280** .337** r 0.0080.1150.2850.2370.0620.0420.0270.0350.2320.4970.4630.470.1050.1410.0880.1190.4910.44 0.0110.045 0.0030.0350.0040.001 N 8585848484848484868685858282838386868787878786868686 OrganizationCoef.-.473** -.429** -0.0490.002.287** .306** .469** .415** 0.0990.1120.1620.139-0.169-.225* .3 02** .399** -.208* -0.131.246* .170* 11.352** .239** .277** .177* r 000.3280.490.0040.001000.1810.1220.070.0750.0640.010.00300.0280.0850.0110.045 00.0070.0050.038 N 8585848484848484868685858282838386868787878786868686 Self-Controlling Coef.-.375** -.259** -.430** -.324** -0.139-0.153.289** 0.153-0.051-0.054.207* 0.140.037-0.0 760.155.233** -.179* -0.139.292** .185* .352** .239** 11.427** .270** r 00.00500.0010.1040.0620.0040.0610.3230.2890.0290.0750.3720.2190.0810.0090.050.0750.0030.03500.007 0 0.004 N 8585848484848484858585858282838386868686868686868686 **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed). Trust Dedication EsteemGeneration Controlling mindedness AggressionTenderImpulsiveness Hard WorkingOrganizationSelf High SelfExtroversionAnxietyCreativity/IdeaStress

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Table D-4. Correlation coefficients of skills/tasks and personality traits. Pearson KendallPearson KendallPearson KendallPearson KendallPears o KendallPearson KendallPearson KendallPearson KendallPearson KendallPearson Kendall Assertiveness Coef.-0.079-0.1570.1770.1690.0890.0570.1 1 0.09-.272** -.245** -0.022-0.049-0.074-0.095-.273** -.277** -.221* -0.1120.1150.13 r0.2510.0620.0630.0510.2270.2930.170.1880.0080.0070.4260.3150.2610.1690.0080.0030.0250.1320.1620.107 N 7575767673737777787877777777787879797676 High Self Coef.-0.078-0.077-0.0090.0270.0020.032-0.115-0.057-0.03-0.007-.212* -.181* -0.153-0.059-.224* -.188* -0.17 1 -0.142-0.063-0.056 Esteem r0.2510.2260.4680.3970.4930.3810.1550.290.4060.4730.030.040.0890.2770.0230.030.0650.0830.2920.299 N 7777787875757979808079797979808080807777 ExtroversionCoef.0.0340.068-0.044-0.1090.110.0980.0780.0610.165.217* 0.0880.1280.0840.1340.0250.086-0.185-0.125-0.1260.106 r0.3840.2540.3520.1470.1760.1780.2480.2740.0730.0160.22 1 0.1070.2340.0910.4130.1950.0510.110.1380.159 N 7676777774747878797978787878797979797676 Anxiety Coef.0.0310.06-0.155-0.1340.0970.1460.1290.114.238* .195* .326** .326** 0.164.174* .316** .362** 0.0410.018-0.097-0.062 r0.3950.2780.0910.0990.2060.0830.130.1320.0170.0260.0020.0010.0760.0410.00200.3590.4310.2040.279 N 7575767674747878797978787878797979797575 Creativity/IdeaCoef.0.0180.0190.013-0.021.253* .344** .212* 0.164.388** .311** .301** .212* .267** 0.151.224* .196* .413** .323** .356** .358** Generation r0.4390.4270.4560.4190.0150.0010.03 1 0.05300.0010.0040.0190.0090.0640.0240.02300.0010.0010 N 7575767674747878797978787878797979797575 Stress Coef.-0.0260.02-0.052-0.042.228* .224* 0.0320.056-0.04-0.0420.0930.0380.0280.040.093.163* .184* 0.156.238* .25 1** r0.4120.420.3250.3370.0250.0150.390.2860.3640.3340.2080.3540.4040.3390.2060.0460.050.0570.0190.008 N 777778787575808080807979808080808 1 817676 Trust Coef.-0.065-0.06-0.08-0.0590.1230.0840.1080.03.272** .230** 0.1850.125.270** .179* 0.179. 180* 0.0830.0290.0180.106 r0.290.2740.2450.2790.1460.2080.17 1 0.3820.0070.010.05 1 0.1060.0080.0330.0560.03 1 0.2320.3830.4380.151 N 7676777775757979808079797979808080807676 Aggression Coef.0.0660.0490.0640.059-.294** -.236* 0.1280.094-.195* -.220* 0.0860.0940-0.071-0.145-.243 ** 0.1050.051-0.064-0.07 r0.290.3140.2940.2810.0060.0120.1350.1750.0450.0130.23 1 0.1760.50.2350.1040.0060.18 1 0.3040.2940.253 N 7373747472727676777776767676777777777373 Tender-Coef.-0.157-0.108-.337** -.324** -0.084-0.03 1 -0.15-0.1470.0380.0870.0530.075.266** .170* .497** .460** .216* 0.0970.1040.106 mindednessr0.090.1450.0010.0010.2390.3840.0940.0720.370.190.32 1 0.230.0090.042000.0280.1670.1870.156 N 7575767674747878797978787878797979797575 Impulsiveness Coef..348** .266** 0.1220.124-0.1-0.0630.0540.0460.0620.0940.0840.035-0.042-0.0290.1240.089-.185* -0.1-0.164-0.1 r0.0010.0040.1430.1090.1950.2660.3170.3190.2920.1670.230.3630.3560.3820.1340.1760.0490.1530.0770.164 N 777778787676808081818080808081818 1 817777 Hard WorkingCoef.0.160.0880.1360.1030.0560.095.321** 332** 0.152.180* 0.1360.162-0.0180.057-.185* -0.11 1 -0.084-0.1130.0250.071 r0.0810.20.1160.1660.3160.190.0020.0010.0880.0410.1150.0620.4360.2860.0490.1360.2270.1360.4140.256 N 7878797976768181818180808181818182827777 OrganizationCoef.-0.0150.003-0.108-0.0820.0680.1210.1350.116.218* .248** .229* .250** 0.155.197* .266** .371** 0.160.128.217* .244** r0.4490.4880.1710.2080.2780.1180.1150.120.0260.0060.02 1 0.0060.0840.020.00800.0750.0960.0290.009 N 7878797976768181818180808181818182827777 Self-Controlling Coef.0.004-0.018-0.052-0.062-0.004-0.0360.070.0130.0590.0020.0960.049.212* 0.1430.0820.0940.1150.0 150.188.177* r0.4870.4270.3260.2720.4860.3640.270.4470.3020.4910.1990.3140.030.0720.2330.1670.1530.4420.0510.044 N 777778787676808081818080808081818 1 817777 DedicationCoef.0.010.062-0.0250.0230.1470.0670.090.0640.1550.1580.0990.0620.1250.0990.090.1020.1770.115.222* .240* r0.4650.2740.4160.4140.1020.2630.2130.2680.0830.060.1920.2740.1350.1630.2120.1530.0570.130.0260.012 N 777778787676808081818080808081818 1 817777 Correlation Test **. Correlation is significant at the 0.01 level (1-tailed). *. Correlation is significant at the 0.05 level (1-tailed). Communication Sensitivity to theComputer LiteracyMathematical other workers E motions of Other s Calculations Manual DexterityPhysical StrengthSpatial PerceptionLeadership Group Interactio n Supervision of

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128 APPENDIX E RESPONSE TABLES Table E-1. Interaction in peer groups. The following responses displayed a gender-based interaction difference, but the connotation cannot be determined: “I think in larger groups women tend to not spea k their opinions as much, generally speaking of course.” “Peer group interaction depends on the personalities of those involved, male or female. I have observed that women are good communicators and once on task can accomplish a great deal. I have also learned that women communicate di fferently than men sometimes resulting in a problem or hiccup of thei r professional growth.” “One or two women in a group could work like some catalyst if properly behaved.” “They are very understanding of goals and tr y to obtain the goals but with minimum disturbance of the group unity.” “Women who want to work in construction in teract very well with the construction team” “Tend to group together.” “Work better, try harder to pl ease coworkers. More assist ance provided to fellow female workers. Sometimes social emotional obstacl es are present (argue about little things).” The following responses displayed a neutral or equal observation a bout interaction in peer groups and differences cannot be determined: “These are difficult questions sinc e so many people are different.” “Close enough to equal” “Interact well… same as men.” “Very well, no different than anyone else.” “Same as men.” “Women appear to work together just as well as men. We have not had any gender issues in this regard.” “The men treat the women as equals and ever yone is mutually respectful. At company meetings men listen to women as much as other men. People interact as friends and colleagues.” “Women get along just fine, ar e well liked and respected.” “They work very well.” “Women do well in peer situations” “Great. There is no differentiation between men and women.” “Well.” “Just as well as men.” “It is hard to answer this… various individuals interact di fferently. I cannot say anything definitive about "women" or "men" on this.”

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129 Table E-1. Continued. The following responses displayed a neutral or equal observation a bout interaction in peer groups and differences cannot be determined: “There is no specific difference in how the women interact.” “Great!” “They interact admirably and equal if not better than men at work.” “Just as well as men, if not better. Subjectivit y and individuality are th e biggest determinants not sex.” “Observations are in PE, APM, PM, Estimating employee groups. Work a nd interact well with peer groups. Leaders in many groups.” “Slightly better than men do.” The following responses displayed that the respondent had no basis for an opinion: “Have not been around women in the trade I work in.” “No peer group experience with women.”

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130 Table E-2. Differences in productivity. The following responses displayed that there was no difference between male and female employee’s productivity at work: “I haven't witnessed any major differences in productivity. Both do their work and both are social. Both ask for a ssistance in equal amounts.” “None” (9 such responses) “No differences” “No difference.” “I have observed no differences be tween the genders as a whole.” “The women tend to be more organized than the men, but both are equally productive.” “No significant difference.” “No difference. They perform equally.” “No observed productivity differences.” “I haven't noticed any stand out differen ces in productivity between men and women.” “None if managed correctly.” “No discernable difference.” “There is no difference between male & female employees in productivity If one is going to work hard it doesn't matter which sex.” The following responses displayed situa tional connotations in their answers: “By design by God most women are not as strong physically as men. If they are operators or something like that they are as productive as me n. Most productivity is a personal attitude and both men and women have more or less producti vity based on their mental attitude.” “When it comes to physical labor it’s just the pl ain and simple truth between muscle mass. Or more specifically testosterone and estrogen, the muscle mass I ha ve is impossible for a woman to have unless they inject testosterone into th eir bodies. Now as far as operating equipment whether it is a grader, loader, back dump or what have you there is no difference but just individual skill of that person.” The following responses displayed that the respondent did not have information in order to make a comparison of productivity: “I did not observe a difference as the jobs were different.” “No opinion.”

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131 Table E-3. Women in the trades. The following comments were found to be more gene ral statements about gender differences rather than attributed to certain trades: “Physically and mentally. Weaker in streng th (most often) Stronge r mentally (60% of time?)” “May not be able to do same physical tasks as well as men. Heavy lifting is an example.” “There are some things that women will not do because of some characteristics.” “Skills involving public relations, human resources.” “It depends on the person, not the gender.” “Based on physical strength only.” “Maybe for tighter to reach places.” “Work with more creativity requirements a nd more communication understanding will be better done by women than men.” “Women do not have the same physical strength.” “Different qualities of women suit different jobs. The same applies for men too.” “I agree that some jobs/trades are more su itable for men but if women are given an opportunity, they will also try to perform well.” “Women are more suited for work that need patience and carefulness, sensitivity or emotion-affected. Such as host of radio.” “Some skills are just better comprehended and performed that are related to the gender.” “If it involves heavy lifting.... a woman's body just isn't made for that... physically, they are not made to do heavy lifting.” “Depends what it is but yes there are true di fferences between male and female that are not sexist but just a fact of li fe. Women are more thought out, have higher pain tolerance, frugal, less apt sudden outbursts of aggressi on and so on but if you study testosterone and estrogen you can find allot of answers there.” “Women typically work better in a setting that is conducive to order and structure whereas a man is better under physical stre ngth requirementsthis is no t always the case as every person is different but, from my experien ce, this is what I have observed.”

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132 LIST OF REFERENCES Andrews, C. L., Mecum, S., and Wilkins, L. "Recruiting Women to the Trades: Marketing Strategies that Work!" Maui Economic Development Board, Women in Technology Project (Aug. 29, 2008). Bishop, Katherine (1991). "Scant Success for Calif ornia Efforts to Put Women in Construction Jobs. The New York Times. (Sept. 12, 2008). Dabke, S., Salem, O., Genaidy, A., & Daraise h, N. (2008). Job satisfaction of women in construction trades. Journal of Construction Engineering & Management, 134 (3), 205216. Eagly, A. H. (2007). Female leadership a dvantage and disadvantage: Resolving the contradictions. Psychology of Women Quarterly, 31 (1), 1-12. Eagly, A. H. & Carli, L. L. (2003). The Female leadership advantage: An evaluation of the evidence. The Leadership Quarterly, 14 (2003), 807-834. Eriksson, K., & Lindholm, T. (2007). Making gender matter: The role of gender-based expectancies and gender identification on women's and men's math performance in Sweden. Scandinavian Journal of Psychology, 48 (4), 329-338. Feingold, A. (1994). Gender differences in personality: A meta-analysis. Psychological Bulletin, 116 (3), 429. Hamilton, C. J. (1995). Beyond sex differences in visuo-spatial processing: The impact of gender trait possession. British Journal of Psychology, 86 (1), 1. Harrison, A. W., Rainer Jr., R. K., & Hochwart er, W. A. (1997). Gender differences in computing activities. Journal of Social Behavior & Personality, 12 (4), 849-868. Hartman, S. J., Griffeth, R. W., Miller, L., & Ki nicki, A. J. (1988). The impact of occupation, performance, and sex on sex role stereotyping. Journal of Social Psychology, 128 (4), 451. Fisher, Christina (2007). "Women: C onstruction's Untapped Resource. Associated Construction Publications . (Sept. 11, 2008). Jauovec, N., & Jauovec, K. (2008). Spatial ro tation and recognizing em otions: Gender related differences in brain activity. Intelligence, 36 (5), 383-393. Kjellberg, K., Lindbeck, L., & Hagberg, M. (1998). Method and performanc e: Two elements of work technique. Ergonomics, 41 (6), 798-816.

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133 Loosemore, M., & Waters, T. (2004). Gender differences in occupational stress among professionals in the construction industry. Journal of Management in Engineering, 20 (3), 126-132. McGlone, M. S., & Aronson, J. (2006). Stereot ype threat, identity salience, and spatial reasoning. Journal of Applied D evelopmental Psychology, 27 (5), 486-493. Menches, C. L., & Abraham, D. M. (2007). Women in Construction Tapping the Untapped Resource to Meet Future Demands. Journal of Construction Engineering and Management, 133 (9), 701-707. Miller, J. (1992). Gender and supe rvision: The legitimization of authority in relationship to task. Sociological Perspectives, 35 (1), 137-162. Moccio, Francine (2006). "New York State Legislative Hearings on the Equal Rights Amendment to the New York State Cons titution. . (Aug. 29, 2008). Moore, Jennifer Dawn (2006). Women in constr uction management: Creating a theory of career choice and development. Ph.D. dissertation, Colorado State Universi ty, United States Colorado. (Publication No. AAT 3226145). (Sept. 8, 2008). Naso, M. (2006). Female work ers find better fitting PPE. Safety & Health, 174 (1), 32-34. Nesby, Tom (1999). "Diversity: New Rea lities for Construction Companies. Seattle Daily Journal and djc.com . (Sept. 6, 2008). Nontraditional Employment for Women (N EW). (2007). Become a NEW Woman. NEW Programs . (Aug.30, 2008). Nordander, C., Ohlsson, K., Balogh, I., Hanss on, G., Axmon, A., Persson, R., et al. (2008). Gender differences in workers with identic al repetitive industrial tasks: Exposure and musculoskeletal disorders. International Archives of Occupational & Environmental Health, 81 (8), 939-947. Ortner, T., & Sieverding, M. (2008). Where ar e the gender differences? Male priming boosts spatial skills in women. Sex Roles, 59 (3), 274-281. Peters, M., & Campagnaro, P. (1996). Do wome n really excel over men in manual dexterity? Journal of Experimental Psychology / Human Per ception & Performance, 22 (5), 1107. Taps, J., & Martin, P. Y. (1990). Gender co mposition, attributional accounts, and women's influence and likeability in task groups. Small Group Research, 21 (4), 471. United States Bureau of Labor Statistics. ( 2007). Women in the labo r force : A databook. Washington, DC: U.S. Dept. of Labor, U.S. Bureau of Labor Statistics.

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134 University of Florida, Office of Institutional Pla nning and Research, (2008). UF Factbook: Enrollment. (Nov. 4, 2008). Walker, H. A., Ilardi, B. C., McMahon, A. M., & Fennell, M. L. (1996). Gender, interaction, and leadership. Social Psychology Quarterly, 59 (3), 255-272.

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135 BIOGRAPHICAL SKETCH Amber Marlene Wangle was born in Columbus Georgia, to John Michael and Arlene Wangle. After graduating summa cum laude fr om Niceville Senior High School in 2001, she began her collegiate education at the University of Florida. After graduating magna cum laude from the Un iversity of Florida with a Bachelor of Design in Architecture, the author continued her studies in pursu it of a Master of Architecture degree. Upon graduation, she decided once agai n to pursue higher education. Amber graduated with a Master of Science in Building Construction in May of 2009 and plans to obtain a professional license to practice both ar chitecture and general construction.