4
Success and Its Evaluation in Science and Engineering

CHAPTER HIGHLIGHTS

Progress in academic careers depends on evaluations of one’s accomplishments by those more senior in a process widely believed to be objective. Research shows, however, that bias negatively affects the evaluations and judgments made about women scientists and engineers and their work. Women consequently are not only underrepresented in numerous science and engineering fields, but are also likely to work in less prestigious institutions than men, to hold lower rank, to take longer to be promoted and tenured, to win fewer awards and honors, and to be named less often to positions of leadership in their institutions and disciplines.

One of the key factors in career advancement is productivity, as measured by the number of published papers that carry the faculty member’s name. Women scientists and engineers have long been considered less productive than men because they published fewer papers. Evidence shows, however, that productivity is not an independent characteristic of individuals but rather a reflection of their positions in the academic hierarchy and the access to resources that those positions make possible. When academic position, available resources, type of institution, and other personal and institutional factors are held constant, men and women scientists and engineers are equally productive. Other evidence indicates that women’s publications have greater average impact than men’s.



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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering 4 Success and Its Evaluation in Science and Engineering CHAPTER HIGHLIGHTS Progress in academic careers depends on evaluations of one’s accomplishments by those more senior in a process widely believed to be objective. Research shows, however, that bias negatively affects the evaluations and judgments made about women scientists and engineers and their work. Women consequently are not only underrepresented in numerous science and engineering fields, but are also likely to work in less prestigious institutions than men, to hold lower rank, to take longer to be promoted and tenured, to win fewer awards and honors, and to be named less often to positions of leadership in their institutions and disciplines. One of the key factors in career advancement is productivity, as measured by the number of published papers that carry the faculty member’s name. Women scientists and engineers have long been considered less productive than men because they published fewer papers. Evidence shows, however, that productivity is not an independent characteristic of individuals but rather a reflection of their positions in the academic hierarchy and the access to resources that those positions make possible. When academic position, available resources, type of institution, and other personal and institutional factors are held constant, men and women scientists and engineers are equally productive. Other evidence indicates that women’s publications have greater average impact than men’s.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering Many people believe that discrimination involves explicit, blatant hostility, but current bias against women scientists and engineers is often subtle, implicit, and unexamined. Under prevailing gender schemas, competent women are often viewed as “overaggressive” and “not nice” whereas traditionally subservient women are seen as “incompetent.” In addition, organizational rules and policies that appear egalitarian often produce different results for men and women. The playing field is not level. Women and minority groups make up an increasing proportion of the labor force. They also are an increasing proportion of the pool of students from which universities can recruit faculty. To capture and capitalize on this talent, policies adopted when the workplace was more homogeneous need to be changed to create organizational structures that manage diversity effectively. Equity efforts need to address the systemic changes required to build and sustain educational, research, and workplace environments that promote effective participation in an increasingly pluralistic society. FINDINGS 4.1 Throughout a scientific or engineering career, advancement depends on judgments of one’s performance by more senior scientists and engineers. A substantial body of research shows these judgments contain arbitrary and subjective components that disadvantage women. The criteria underlying the judgments developed over many decades when women scientists and engineers were a tiny and often marginal presence and men were considered the norm. 4.2 Gender bias—often unexamined, and held and acted on by people of both sexes who believe themselves unbiased—has affected many women scientists’ chances of career progress. Minority-group women face the double bind of racial and gender bias. 4.3 Incidents of bias against individuals not in the majority group tend to have accumulated effects. Small preferences for the majority group can accumulate and create large differences in prestige, power, and position. In academic science and engineering, the advantages have accrued to white men and have translated into larger salaries, faster promotions, and more publications and honors relative to women. 4.4 Women have the qualities needed to succeed in academic careers and do so more readily when given an equal opportunity to achieve. For example, publication productivity is one of the most important factors by which scientists are evaluated for hiring, promotion, and

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering tenure. Women scientists’ publication productivity has increased over the last 30 years and now matches men’s. The critical factor affecting publication productivity is access to institutional resources; marriage, children, and elder-care responsibilities have minimal effects. 4.5 Career impediments based on gender or racial or ethnic bias deprive the nation of an important source of talented and accomplished researchers. RECOMMENDATIONS 4.1 Trustees, university presidents, and provosts should provide clear leadership in changing the culture and structure of their institutions to recruit, retain, and promote women—including minority women— into faculty and leadership positions. 4.2 University leaders should work with their faculties and department chairs to examine evaluation practices to focus on quality of contributions and their impact. 4.3 Deans, department chairs, and their tenured faculty should take the responsibility for creating a productive environment and immediately implement programs and strategies shown to be successful in minimizing the effect of biases in recruiting, hiring, promotion, and tenure. 4.4 Faculties and their Senates should initiate a full faculty discussion of climate issues. 4.5 Universities should provide management and leadership training for deans, department heads, search committee chairs, and other faculty with personnel management responsibilities; they should also provide management training to new faculty as part of a professional development core. 4.6 University leaders should, as part of their mandatory management efforts, hold leadership workshops for deans, department heads, search committee chairs, and other faculty with personnel management responsibilities, that include an integrated component on diversity and strategies to overcome bias and gender schemas and strategies for encouraging fair treatment of all people. It is crucial that these workshops are integrated into the fabric of the management of universities and departments. 4.7 Deans, department chairs, and their tenured faculty should develop and implement programs that educate all faculty members and

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering students in their departments on unexamined bias and effective evaluation; these programs should be integrated into departmental meetings and retreats, and professional development and teacher-training courses. For example, such programs can be incorporated into research ethics and laboratory management courses for graduate students, postdoctoral scholars, and research staff and can be part of management leadership workshops for faculty, deans, and department chairs. 4.8 Scientific and professional societies should provide professional development training for members that includes a component on bias in evaluation; develop and enforce guidelines to ensure significant representation of women on meeting speaker lists, on editorial boards, and in other significant leadership positions; and work to ensure that women are recognized for their contributions to the nation’s scientific and engineering enterprise through nominations for awards and leadership positions. 4.9 Honorary societies should review their nomination and election processes to address the underrepresentation of women in their memberships. 4.10 Journals should examine their entire review process, including the mechanisms by which decisions are made to send a submission to review, and take steps to minimize gender bias, such as blinded reviews. 4.11 Federal funding agencies and foundations should work with scientific and professional societies to host mandatory national meetings that educate members of review panels, university department chairs, and agency program officers about methods that minimize the effects of gender bias in evaluation. The meetings should be held every 2 years for each major discipline and should include data and research presentations on subtle biases and discrimination, department climate surveys, and interactive discussions or role-modeling. Program effectiveness should be evaluated on an ongoing basis. 4.12 Federal funding agencies should collect, store, and publish composite information on demographics, field, award type and budget request, review score, and funding outcome for all funding applications. 4.13 Funding organizations should expand support for research on the efficacy of organizational programs designed to reduce gender bias, and for research on bias, prejudice, stereotype threat, and the role of leadership in achieving gender equity. To build a successful academic career, a scientist or engineer must succeed—and be seen by colleagues and superiors to have succeeded—at

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering each of a number of increasingly demanding stages of development. Judgments of performance are widely thought to be objective, but a substantial body of research shows that they are significantly affected by biases. The effect of any specific instance of bias may not in itself be large— receiving a somewhat lower evaluation or a less enthusiastic recommendation than would be true in the absence of bias, not being invited to chair a session at a meeting, or being excluded from conversations in a friendship network. Such instances of bias would not prevent a person from doing research or pursuing a career. A growing body of evidence shows, however, that such incidents of bias tend to accumulate. In a highly competitive field in which reputation and influence are crucial aspects of professional standing, small preferences can accumulate into large differences in prestige, power, and position (Box 1-4). In academic science and engineering, the advantages accrued to white men have translated into increased salaries, faster promotions, and more publications and honors relative to women. BUILDING A CAREER A career has four interlocking dimensions: education, position, productivity, and recognition.1 Whether a given scientist or engineer succeeds in building such a career depends on a number of factors, some personal and some institutional—as well as luck or happenstance. Does he or she possess the qualities of intellect, character, and personality needed to succeed when there is high-stakes competition? Does he or she work on research questions that produce results worthy of publication and citation? Does he or she succeed in obtaining adequate funding to carry out research? Does he or she develop relationships that help to advance the research and the career? Do the institutions where he or she was educated and trained and where he or she attempts to establish and further a career provide advantages or impose disadvantages that make success more or less likely? Productivity College and university faculty members fulfill three main functions: teaching, research, and service in various capacities, such as committee members or department officials involved in running the institution. For purposes of hiring and advancement to higher rank, however, research productivity—defined as authorship of peer-reviewed publications—is 1 MF Fox and JS Long (1995). Scientific careers: Universalism and particularism. Annual Review of Sociology 21:45-71. For a discussion of education and position, see Chapter 3.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering weighed most heavily,2 even though efforts have been made to expand the definition of scholarship to include teaching, the integration of knowledge, grants awarded, and applications of research in addition to original discoveries.3 Publications, particularly those in high-prestige journals or conference proceedings, carry the greatest weight.4 That is true regardless of whether the responsibilities of the faculty member’s position actually involve doing research or instead focus on administration, teaching, or service. Faculty productivity measured by quantity of publications has also been shown to correlate with stamina and opportunity but not with creativity or measured intelligence.5 And studies show that teaching and research have opposite relationships to publication productivity: increased time commitments to teaching are associated with decreased publication productivity.6 Observers have argued that emphasis on number of publications overvalues the work of men scientists and engineers at the expense of women because of the unequal allocation of tasks that characterizes academic life. Women, on average, devote more time than men to teaching and service, while men, on average, devote more time than women to research.7 Recent evidence from faculty surveys indicates that more women than men faculty feel that mentoring as a service activity is undervalued by their department (Figure 4-1). Some have suggested that discrepancy reflects value differences between the sexes, namely that women give greater emphasis to such nurturing activities as teaching and advising students and men give greater emphasis to competition. Others argue that the discrepancy reflects the fact that women generally have less power and less opportunity to obtain positions at research universities, where support systems and resources clearly increase faculty productivity.8 2 M Skolnik (2000). Does counting publications provide any useful information about academic performance? Teacher Education Quarterly 27(2):15-25. 3 E Boyer (1990). Scholarship Reconsidered: Priorities of a Professoriate. Princeton, NJ: Princeton University Press. 4 Skolnik (2000), ibid; J Long, P Allison, and R McGinnis (1993). Rank advancement in academic careers: Sex differences and the effects of productivity. American Sociological Review 58(8):703-722. 5 MF Fox (1985). Publication, performance and reward in science and scholarship. In Higher Education: Handbook of Theory and Research, Vol. 1, ed. JC Smart, New York: Agathon. 6 MF Fox (1992). Research, teaching, and publication productivity: Mutuality versus competition in academia. Sociology of Education 65(4):293-305. 7 SM Park (1996). Research, teaching and service: Why shouldn’t women’s work count? The Journal of Higher Education 67:46-84; EE Gottleib and B Keith (1997). The academic research-teaching nexus in eight advanced-industrialized countries. Higher Education 34:397-420. 8 Fox (1985), ibid; H Dundar and DR Lewis (1998). Determinants of research productivity in higher education. Research in Higher Education 39(6):607-631.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering FIGURE 4-1 Individual and perceived institutional value of student mentoring, by rank and sex. NOTE: The survey asked faculty to rate whether they valued mentoring more, the same, or less than they perceived their department valued mentoring. SOURCE: University of California Faculty Climate Survey, 2003. Available at http://www.ucop.edu/acadadv/berkeley-response/faculty-climate.pdf. Especially during the probationary years, graduate students, postdoctoral scholars, and assistant professors feel intense pressure to prove that they are not only productive, but serious about their science and engineering careers. They often spend very long hours at their work and try to show a total commitment to an academic career. “By its nature, academic work is potentially boundless: there is always one more question to answer; one more problem to solve; one more piece to read, to write, to see, or to create.”9 In addition, for scientists or engineers working on federal grants, the granting agencies impose time accounting requirements.10 9 JW Curtis (2004). Balancing work and family for faculty: Why it’s important. Academe 90(6), http://www.aaup.org/publications/Academe/2004/04nd/04ndtoc.htm. 10 J Couzin (2006). US rules on accounting for grants amount to more than a hill of beans. Science 311:168-169.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering Some have suggested that a postdoctoral fellow intent upon a research career should be spending 60-80 hours per week in the laboratory and clinical fellows 80-120 hours per week.11 The National Science Foundation (NSF) has determined the average workweek for science and engineering faculty to be 50.6 hours per week.12 At one research university, faculty with and without children reported engaging in professional work 51-60 hours per week, but women faculty with children spend substantially more time than men faculty with children on household and child-care responsibilities (Figure 4-2).13 Those findings mirror what is seen in a national sample of science and engineering doctorates. Men engage in professional work an average of 0.7 hour per week more than women, but the difference was associated with having children living in the household. Men and women without children reported working 49 hours per week, and women with children—but not men with children—reported working 46 hours per week.14 Those statistics belie the nature of work for a scientist or engineer, whose productivity does not depend solely on total hours logged in the laboratory. Indeed, other sorts of work—including reading literature, going to meetings, and discussions with colleagues—may occur off site but are no less important. For persons with major caregiving responsibilities, particularly the care of children or other dependent family members, the limitless time demands of a competitive academic career present a major challenge. The great majority of those bearing caregiving responsibilities are women, and their effort in their family responsibilities does not count as “work” in the academic schema, but rather as a distraction from work. 11 S Kern (2002). Fellowship Goals for PhDs and MDs: A primer on the molecular biology postdoctoral experience. Cancer Biology and Therapy 1:74-85. Kern notes the total hours include research and reading; he also notes that the routine 80-120 hours in clinical training “may be incompatible with a researcher’s need for creativity and precision.” 12 TB Hoffer and K Grigorian (2005). All in a Week’s Work: Average Workweeks of Doctoral Scientists and Engineers (NSF 06-302). Arlington, VA: National Science Foundation, http://www.nsf.gov/statistics/infobrief/nsf06302/nsf06302.pdf. 13 WH Gmelch, PK Wilke, and NP Lovrich (1986). Dimensions of stress among university faculty: Factor-analytic results from a national survey. Research in Higher Education 24:266-286; MA Mason and M Goulden (2004). Marriage and baby blues: Redefining gender equity in the academy. Annals of the American Academy of Political and Social Science 596(1):86-103, http://ann.sagepub.com/cgi/reprint/596/1/86. 14 Hoffer and Grigorian (2005), ibid.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering FIGURE 4-2 University of California faculty, 30-50 years old, self-reported hoursTotal Hours per Week per week engaged in professional work, housework, and caregiving. SOURCE: Adapted from: MA Mason, A Stacy, and M Goulden (2003). University of California Faculty Work and Family Survey, http://ucfamilyedge.berkeley.edu/workfamily.htm. The “ideal worker” is someone whose commitment to work is unlimited by child bearing or rearing—i.e., a man. Success in academia today continues to be aligned with traditional masculine stereotypes of autonomy, competitiveness and heroic individualism. The ‘ideal worker’ is someone for whom work is primary, the demands of family, community, and personal life secondary, and time to work unlimited. —Ellen Ostrow, clinical psychologist and founder of Lawyers Life Coach15 Sex Differences in Publication Productivity Why is publication productivity important? It is through publications that research results are communicated and verified. Publication productivity is both the cause and the effect of status in science and engineering. 15 E Ostrow (2002). The backlash against academic parents. Chronicle of Higher Education (February 22), http://chronicle.com/jobs/2002/02/2002022202c.htm.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering Several researchers have shown that publication productivity reflects and partially accounts for the depressed rank in status of women in science and engineering.16 However, this assumes that it is the number of papers that is important and does not account for differences in the impact of papers. In decades past, data have shown an apparent gender gap in the numbers of papers published by men and women faculty. In a study of scientists who received PhDs in 1969-1970, Cole and Zuckerman estimated that, on average, women published slightly more than half (57%) as many papers as men.17 Little information is available on publication rates for minority-group scientists.18 The root of the difference in publication productivity is an essential question. Several studies have examined the effect of family-related factors. Although more women than men leave academe because of family responsibilities, research on the effects of marriage, children, or elder-care responsibilities has yielded mixed results.19 The critical variable appears to be access to resources. A recent longitudinal analysis by Xie and Shauman of faculty in postsecondary institutions in 1969, 1973, 1988, and 1993 shows that the sex difference in research productivity has declined—from a female:male ratio of 0.580:1 in 1969 to 0.817:1 in 1993. In that period, the primary factor affecting women scientists’ research productivity was their overall structural position, such as institutional affiliation and rank. When type of institution, teaching load, funding level, and research assistance are factored in, the productivity gap disappears.20 16 G Sonnert and G Holton (1996). Career patterns of women and men in the sciences. American Scientist 84:63-71; EG Creamer (1998). Assessing faculty publication productivity: Issues of equity (ASHE-ERIC Higher Education Report 26(2)). Washington, DC: George Washington University; LJ Sax, S Hagedorn, M Arredondo, and FA Dicrisi (2002). Faculty research productivity: Exploring the role of gender and family-related factors. Research in Higher Education 43(4):423-446; MF Fox (2005). Gender, family characteristics, and publication productivity among scientists. Social Studies of Science 35(1):131-150. 17 JR Cole and H Zuckerman (1984). The productivity puzzle: Persistence and change in patterns of publication of men and women scientists. Advances in Motivation and Achievement 2:217-258; see also JS Long (1992). Measures of sex differences in scientific productivity. Social Forces 71:159-178; there appears to be a publication productivity gap between men and women and white and minority students in graduate school, see Chapter 3 and MT Nettles and CM Millett (2006). Three Magic Letters: Getting to PhD. Baltimore, MD: Johns Hopkins Press. 18 MF Fox and JS Long (1995). Scientific careers: Universalism and particularism. Annual Review of Sociology 21:45-71; W Pearson (1985). Black Scientists, White Society, and Colorless Science: A Study of Universalism in American Science. Millwood, NY: Associated Faculty. 19 Reviewed in LJ Sax, S Hagedorn, M Arredondo, and FA Dicrisi (2002), ibid. 20 Y Xie and KA Shauman (1998). Sex differences in research productivity: New evidence about an old puzzle. American Sociological Review 63(6):847-870.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering Another analysis provides a clear illustration of the correlation between productivity, institutional affiliation, and rank.21 Overall, men academic scientists and engineers produced 30% more publications than women academic scientists and engineers, but when men at Research I universities were compared with women at the same type of institution, the productivity gap fell to 25%. Women were much more likely to be in non-tenure-track posts than men, and comparing only scientists and engineers who held faculty positions reduced the productivity gap to 13%. Focusing on tenured faculty members found tenured men with only 8% more publications than their women tenured colleagues. The difference in publication productivity between men and women who are full professors of science or engineering at the Research I institutions was under 5%. The effect of a scientist’s institutional affiliation on his or her productivity is so great that the prestige of the department or university has been found to affect scientists’ productivity, rather than the other way around. Prestige serves as a symbolic stand-in for an array of characteristics that can foster or hamper productivity, including financial, physical, and staff resources and intellectual environment. Evidence shows that when scientists move to more prestigious institutions, their productivity increases.22 Another essential question is whether number of papers is the appropriate metric of productivity. In a study of biochemists, Long found that articles by women received, on average, more citations than articles with men primary authors.23 Some have argued that both quantitative and qualitative measures of productivity should be taken into account in making important decisions about a scientist’s career.24 Indeed, recent metrics have been developed to measure citations of an article—its “impact factor”—as well as the prestige of the journal in which it is published.25 Recognition Another indicator of scientific productivity, and one especially germane to career advancement, is recognition in the field. Being invited to 21 National Research Council (2001). From Scarcity to Visibility: Gender Differences in the Careers of Doctoral Scientists and Engineers. Washington, DC: National Academy Press, http://www.nap.edu/catalog/5363.html. 22 P Allison and S Long (1990). Departmental effects on scientific productivity. American Sociological Review 55:119-25. 23 JS Long (1992). Measures of sex differences in scientific productivity. Social Forces 71:159-178. 24 Sonnert and Holton (1996), ibid. 25 P Ball (2006). Prestige is factored into journal ratings. Nature 439(16):770-771, http://www.nature.com/nature/journal/v439/n7078/pdf/439770a.pdf.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering FIGURE B4-6A FIGURE B4-6B Actual percentages of women and minority faculty hired.f Departments who sent at least one faculty member to a workshop showed a 19% increase in the percentage of their new assistant professors who were women, compared to a 23% decrease for those departments that did not participate (FigureB4-6B).    fFine and Sheridan (2006), ibid.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering These measures indicate that WISELI’s approach to educating search committee chairs appears to be working, although many other factors such as the motivation of the individual search committee chairs and departments are likely to also play an important role. WISELI plans to continue implementing workshops across the UW-Madison campus, expanding them beyond faculty and administrative searches to searches for other staff as well. One large college made participation in these workshops mandatory for all search committee chairs beginning in 2005/2006. WISELI is also visiting other campuses to offer a day-long session, “Searching for Excellence & Diversity: Implementing Training for Search Committees,” to help universities, university systems, and/or regional collectives develop and present search workshops on their own campuses.g    ghttp://wiseli.engr.wisc.edu/initiatives/hiring/ImplementingTraining.htm. versity of Michigan has its STRIDE (Strategies and Tactics for Recruiting to Improve Diversity and Excellence) program,54 which uses senior professors of science and engineering who have been trained by social scientists to work with recruitment committees to overcome biases. University administrators can make departments accountable by making participation in such programs a condition for undertaking a faculty search. Building in a measure of accountability reduces the use of stereotypes in choosing job candidates.55 Understanding Discrimination56 Although women today in the United States have many more opportunities than women of previous generations, many societal traditions inhibit their full participation in the technical workforce. Women have been struggling for access into universities and entrance into the labor force since the 54 University of Michigan STRIDE Web site, http://sitemaker.umich.edu/advance/stride. See AJ Stewart, D LaVaque-Manty, and JE Malley (2004). Recruiting women faculty in science and engineering: Preliminary evaluation of one intervention model. Journal of Women and Minorities in Science and Engineering 10(4):361-375. 55 PE Tetlock (1985). Accountability: A social check on the fundamental attribution error. Social Psychology Quarterly 48:227-236. 56 See Appendix C for a discussion of the theories of discrimination. Excerpted from National Research Council (2004). Measuring Racial Discrimination. Washington, DC: The National Academies Press, pp. 55-70, http://fermat.nap.edu/catalog/10887.html.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering middle of the 19th century.57 But, admission was only half the battle. Women were often co-opted into the science and engineering professions to provide lower-cost labor necessary to combat temporary workforce shortages. In addition, as described in Chapter 5, when women are hired into faculty or upper management, institutions do not provide contexts conducive to their productive potential or retention.58 Subtle, Implicit, or Unexamined Bias Even as gender equity gains ground and a national consensus has developed that explicit racial hostility is abhorrent,59 people may still hold prejudiced attitudes, stemming in part from the US history of overt sex and racial prejudice. Although prejudicial attitudes do not necessarily result in discriminatory behavior with adverse effects, the persistence of such attitudes can result in unconscious and subtle forms of discrimination in place of more explicit, direct hostility. Such subtle prejudice is often abetted by differential mass-media portrayals60 and by de facto segregation in education and occupations. All manifestations of subtle prejudice constitute barriers to full equality of treatment. Subtle prejudice is much more difficult to document than more overt forms, and its effects on discriminatory behavior are more difficult to capture. However, subtle does not mean trivial or inconsequential; subtle prejudice can result in major adverse effects. More recently, legal scholars have begun to use the term unexamined to describe such discriminatory behavior, arguing that it shifts the burden of proof and acknowledges that such behavior can be changed.61 57 BM Solomon (1985). In the Company of Educated Women: A History of Women and Higher Education in America. New Haven, CT: Yale University Press; R Oldenziel (2000). Multiple entry visas: Gender and engineering in the US, 1870-1945. In Crossing Boundaries, Building Bridges: Comparing the History of Women Engineers 1870s-1990s, eds. A Canal, R Oldenziel, and K Zachmann, Amsterdam: Overseas Publishers Association. 58 C Vogt (2006). Women’s participation in ICT careers in industrialized nations. In Explaining Gendered Occupational Outcomes, eds. J Eccles and H Watt. Washington, DC: American Psychological Association. 59 R Inglehart and P Norris (2003). Rising Tide: Gender Equality and Cultural Change. New York: Cambridge University Press; LD Bobo (2001). Racial attitudes and relations at the close of the twentieth century. In America Becoming: Racial Trends and their Consequences, Vol. 1, eds. NJ Smelser, WJ Wilson, and F Mitchell. Washington, DC: National Academy Press. 60 PG Davies, SJ Spencer, DM Quinn, and R Gerhardstein (2002). Consuming images: How television commercials that elicit stereotype threat can restrain women academically and professionally. Journal of Personality and Social Psychology 33:561-578. 61 JC Williams (2006). Moving beyond the “Chilly Climate” to a new model for spurring organizational change. In Biological, Social, and Organizational Components of Success for Women in Science and Engineering. Washington, DC: The National Academies Press.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering Pervasive, unexamined gender bias has played a major role in limiting women’s opportunities and careers because American culture generally stereotypes science, mathematics, and engineering as domains appropriate to white men and much less suitable for women or members of racial or ethnic minorities. If gender bias takes a so-called benevolent form, women are viewed as pure and morally superior, although not suited for male occupations. Under a hostile form of gender bias, women who aspire to traditionally masculine roles are seen as undermining or attacking the rightful prerogatives of men. The combination of those biases often causes competent women to be perceived as “not nice” or even “overly aggressive” and traditionally subservient women to be perceived as “incompetent” and “trivial.”62 As described in Chapter 2, in-group and out-group stereotypes can lead to lower test performance and reduce confidence and can lead some women and members of underrepresented minorities to develop less interest in pursuing science- and mathematics-based careers, even when they major in those fields. It can also affect students’ interest in taking on the leadership roles that are necessary for success in academic research.63 The tendency to see women and minority-group members as less competent than white men and their accomplishments as less worthy and significant is a prominent component of the “glass ceiling,” the well-known complex of attitudes and biases that keeps women and minorities in many organizations and professions out of the most powerful, influential, and prestigious positions because they are assumed to be unfit for leadership.64 Stereotyping and cognitive bias thus create a “built-in headwind” for women and minorities in the sciences and engineering. 62 P Glick and S Fiske (1996). The Ambivalent Sexism Inventory: Differentiating hostile and benevolent sexism. Journal of Personality and Social Psychology 70:491-512. 63 CM Steele and J Aronson (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology 69:797-811; M Inzlicht and Ben-Zeev (2000). A threatening intellectual environment: Why women are susceptible to experience problem-solving deficits in the presence of men. Psychological Science 11:365-371; J Keller (2002). Blatant stereotype threat and women’s performance: Self-handicapping as a strategic means to cope with obtrusive negative performance expectations. Sex Roles: A Journal of Research 47:193-198; T Schmader, M Johns, and M Barquissau (2004). The costs of accepting gender differences: The role of stereotype endorsement in women’s experience in the math domain. Sex Roles: A Journal of Research 50:835-850; PG Davies, SJ Spencer, and CM Steele (2005). Clearing the air: Identity safety moderates the effects of stereotype threat on women’s leadership aspirations. Journal of Personality and Social Psychology 88:276-287. 64 JC Williams (2004). Hitting the maternal wall. Academe 12(6), http://www.aaup.org/publications/Academe/2004/04nd/04ndwill.htm; JC Alessio and J Andrzejski (2000). Unveiling the hidden glass ceiling. American Sociological Review 26 (2):311-315.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering The main effect of subtle prejudice seems to be to favor the in group rather than to directly disadvantage the out group.65 One might, for example, fail to promote someone on the basis of race, perceiving the person to be deferential, cooperative, and “nice” but essentially incompetent, whereas a comparable in-group member might receive additional training or support to develop greater competence. Conversely, one might acknowledge an out-group member’s exceptional competence but fail to see the person as sociable and comfortable—and therefore not fitting in, not “one of us,” and less collegial—and on that account fail to promote the person as rapidly. The Case for Diversity: “There Goes the Neighborhood?” There have been dramatic changes in workforce demographics over the last 40 years. As discussed in Chapter 1, women and minority groups make up an increasing proportion of science and engineering students and the technical labor force.66 The benefits of workforce diversity seem clear in knowledge-based innovative work requiring creativity and flexibility.67 In the past decade, a number of reports and popular books have touted the benefits of workplace diversity,68 connecting it to enhanced group problem solving, increased creativity, and increased profits.69 A vast and growing body of research provides evidence that a diverse student body, faculty, and 65 MB Brewer and R Brown (1998). Intergroup relations. In eds. D Gilbert, ST Fiske, and G Lindzy, The Handbook of Social Psychology, 4th edition. New York: McGraw-Hill. 66 See, for example, A Antonio (2003). Diverse student bodies, diverse faculties. Academe 89(6):14-18. 67 M Polyani (1962). The Republic of Science: Its political and economic theory. Minerva 1:54-74; NL Johnson (2000). Developmental Insights into Evolving Systems: Roles of Diversity, Non-selection, Self-organization, Symbiosis. Paper presented at Seventh International Conference on Artificial Life. Portland OR, August 1-6; see also review in SE Jackson, KE May, and K Whitney (1995). Understanding the dynamics of diversity in decision-making teams. In Team Effectiveness and Decision-Making in Organizations, eds. RA Guzzo and E Salas. San Francisco: Jossey-Bass. 68 See, for example, WB Johnstone and AE Packer (1987). Workforce 2000: Work and Workers for the Twenty-First Century. Indianapolis, IN: Hudson Institute; A Morrison (1996). The New Leaders: Leadership Diversity in America. San Francisco: Jossey-Bass. 69 CJ Nemeth (1985). Dissent, group process, and creativity: The contribution of minority influence. Advances in Group Processes 2:57-75; CJ Nemeth (1995). Dissent as driving cognition, attitudes, and judgments. Social Cognition 13:273-291;TH Cox (1993). Cultural Diversity in Organizations: Theory, Research, and Practice. San Francisco: Berrett-Keohler; PL McLeod, SA Lobel, and TH Cox (1996). Ethnic diversity and creativity in small groups. Small Group Research 27:248-265; S Nelson and G Pellet (1997). Shattering the Silences

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering staff benefits the joint missions of teaching and research.70 However, if the structural conditions and individual perspectives do not exist to harness their benefit, diverse workgroups can lead to increased workplace tension, team fragmentation, and increased staff turnover.71 Ineffective processes and policies are manifested as workplace bias: differences in career outcomes by gender or race/ethnicity that are not attributable to the differences in skills, qualifications, interests, or preferences that individuals bring to the employment setting.72 Diversity and discussions of it can be turbulent and uncomfortable, but it also is clarifying, illuminating, leading to a deeper understanding of one’s self and one’s world. Diversity advances innovation. Diversity powers excellence. —Shirley Jackson, President, Rensselaer Polytechnic Institute (2005)73 Businesses and universities realize that to capture and capitalize on this talent, they need to change policies adopted when the workplace was more homogeneous and create new organizational structures.74 Most organizational efforts have focused on race and gender, but many also incorporate other aspects of diversity, including socioeconomic status, ethnic heritage, sexual orientation, and disability status.75 At the same time, organizations must consider increasing challenges to the concept of affirmative action and the discontinuation of programs seen to be providing advantage to any [videorecording]. San Francisco: Gail Pellet Productions; A Antonio (2002). Faculty of color reconsidered: Reassessing contributions to scholarship. Journal of Higher Education 73:582-602; CSV Turner (2000). New faces, new knowledge. Academe 86:34-37; JF Milem (2003). The educational benefits of diversity: Evidence from multiple sectors. In Compelling Interest: Examining the Evidence on Racial Dynamics in Higher Education, eds. M Chang, et al. Stanford, CA: Stanford Education; DA Thomas (2004). Diversity as strategy. Harvard Business Review 82(9):98-108. 70 See WISELI’s Benefits and Challenges of Diversity, http://wiseli.engr.wisc.edu/initiatives/climate/Benefits_Challenges.pdf. 71 See review by Jackson, May, Whitney (1995), ibid. 72 WT Bielby (2000). Miminizing workplace gender and racial bias. Contemporary Sociology 29(1):120-129. 73 UCSC Chancellor’s Inaugural Symposium, November 3, 2006, http://celebration2005.ucsc.edu/symposium.asp. 74 WB Johnstone and AE Packer (1987), ibid. 75 See, for example, M Loden (1995). Implementing Diversity. Burr Ridge, IL: McGrawHill.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering specific group.76 Equity efforts need to address not just individual needs but also the systemic changes needed to build and sustain educational, research, and workplace environments that promote effective participation in an increasingly pluralistic society. As described below (Box 4-7), such structures would include proactive recruiting, programs to enhance team-building and interpersonal skills, compensation equity, family friendly policies, mentoring and career development programs for junior and senior employees, and accountability through annual appraisals and evaluations. Accountability and Evaluation Program evaluation must be an integral part of any diversity initiative. Models for some best practices have begun to emerge from some ADVANCE institutions (Box 5-5).77 However, none of the ADVANCE institutions have to date completed their 5-year institutional transformation grant, so evaluation of the success of these programs is not possible. Progress can be gleaned from annual reports to NSF78 and on many of the individual program Web sites. Effective assessment is an iterative self-diagnostic process. It ideally involves continuous cycles of program improvement and refinement. A program should incorporate a hypothesis, a set of measurable goals, and should collect baseline (formative) and outcomes (summative) data to test that hypothesis. Reasoned analyses and plans are followed by “experimental” trials with continuous testing, learning, and program refinement from those planned trials. A percentage of total program funding should be allotted to evaluation activities and an individual should be designated to be responsible for data collection and analysis; 5% of total project funding is a common allocation for evaluation in federal programs.79 76 G Custred and T Wood (1996). California’s Proposition 209, http://www.acri.org/209/209text.html; Gratz v. Bollinger, No. 02-516, 123 S. Ct. 2411 (2003); Grutter v. Bollinger, No. 02-241, 123 S. Ct. 2325 (2003); A Klein (2004). Affirmative-action opponents suffer setbacks in Colorado and Michigan. Chronicle of Higher Education 50(31):A23; R Roach (2005). Ford diversity fellows urged to defend affirmative action. Diverse Issues in Higher Education, http://www.diverseeducation.com/artman/publish/article_4898.shtml; P Schmidt (2006). From “Minority” to “Diversity”. The transformation of formerly race-exclusive programs may be leaving some students out in the cold. Chronicle of Higher Education 52(22): A24; P Schmidt (2006). Southern Illinois U. and Justice Dept. near accord on minority fellowships. Chronicle of Higher Education 52(22):A26; R Clegg (2006). Faculty hiring preferences and the law. Chronicle of Higher Education 52(37):B13. 77 See SV Rosser (2006). Creating an inclusive work environment. In: Biological, Social, and Organizational Components of Success for Women in Science and Engineering. Washington, DC: The National Academies Press. 78 Available at http://www.nsf.gov/advance. 79 National Research Council (1996). The National Scholars Program: Excellence with Diversity for the Future. Washington, DC: National Academy Press.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering FOCUS ON RESEARCH BOX 4-7 Making Diversity Work “If you think managing diversity is a program, you don’t get it.”a Considerable research has shown the barriers limiting the appointment, retention, and advancement of women faculty. The question is how to move beyond these barriers and make diversity work. An evaluation of a wide-ranging campus diversity initiative in the University of California system provides specific lessons for academe. Programs that were effective had three key components: the campus had a framework for monitoring progress, a commitment to analyze and use data for organizational change, and a commitment to take corrective action.b These results mirror what is found in other organizations that have implemented successful diversity management programs. Several researchers have examined program efficacy using a variety of techniques, including tracking of workforce composition and employment practices,c and case studies in industryd and federal agencies.e While there are some important differences, there are some common factors that successful programs—those shown to improve workforce diversity—exhibit. These benchmarks of success are: Management involvement (CEO, President)—resource commitments, internal communication of goals, alignment of strategic goals and organizational mission. Close tailoring of diversity initiative to organizational needs, starting with performance of an organizational survey to identify demographics, issues, and needs. Program not specific to a demographic group.f Changes individual behavior. Changes personnel systems and existing organizational procedures and practices. Involves organizational development—participation of top managers, sequencing of educational programs so that managers back up training of nonsupervisory staff, long-term effort to reach a large proportion of employees, and considerations of the length and depth of programs. Incorporates measurables and accountability—regular monitoring of patterns of job segregation, pay, and career advancement by gender and race/ethnicity; and explict evaluation of managers and supervisors in contributing to initiative goals. Industries that have large research and development (R&D) components may be most likely to hold lessons for academia. In this context, several actions are correlated with increased workforce diversity:g Mentoring programs have been highly effective in moving white and African American women and African American men into management. Culture audits and surveys of workers have resulted in increases in white and African American women in management, whereas they show mixed effects in non-R&D industries. Targeted recruitment is particularly effective in R&D industries.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering Overall, these findings support the creation of systems of authority and accountability (diversity committees, affirmative action plans) (Box 6-2), the use of targeted searches and incentives (Box 3-6), the use of surveys to assess university culture (Box 6-7), and the implementation of mentoring programs (Box 6-3). While diversity training is helpful in R&D intensive industries, it is important to note that corporate diversity training is very different from the sort of diversity initiatives found in the ADVANCE programs (Box 5-5), in which academic scientists rather than hired consultants lead training and create ongoing feedback and learning systems (Boxes 4-3, 4-4, and 4-6). Such training systems are akin to diversity committees, which are quite effective in both R&D industries and elsewhere. To derive maximal benefits from diversity, members of academic communities must show respect for each other’s cultural and stylistic preferences and awareness of unconscious assumptions and behaviors that may influence interactions. Only when differences are openly discussed and learned from do the positive effects of diversity accrue; open discussion makes it possible for the groups to create psychological safety.h The goal is to create a climate in which everyone feels personally safe, listened to, valued, and treated fairly and with respect.    aF Miller (1992). Discussant commentary. Leadership Diversity Conference: Beyond Awareness into Action. Center for Creative Leadership, Greensboro, NC.    bDG Smith, S Parker, AR Clayton-Pedersen, JF Moreno, and DH Teraguchi (2006). Building Capacity: The Study of Impact of The James Irvine Foundation Campus Diversity Initiative. Irvine, CA: The James Irvine Foundation.    cA Kalev, F Dobbin, and E Kelly (2006). Best Practices or Best Guesses? Diversity Management and the Remediation of Inequality (Working Paper). Cambridge, MA: Harvard University, http://www.wjh.harvard.edu/~dobbin/cv/working_papers/eeopractice1.pdf.    dM Bendick, ML Egan, and SM Lofhjelm (1998). The Documentation and Evaluation of Anti-Discrimination Training in the United States. Geneva: International Labor Organization; JA Gilbert, BA Stead, and JM Ivancevich (1999). Diversity management: A new organizational paradigm. Journal of Business Ethics 21:61-76; R Ely (2004). A field study of group diversity, participation in diversity education programs and performance. Journal of Organizational Behavior 25(6):755-780.    eKC Naff and JE Kellough (2003). Ensuring employment equity: Are federal diversity programs making a difference? International Journal of Public Administration 26(12):1307-1336.    fSome research indicates that broad diversity initiatives may not help, and in some cases may hinder, the promotion of minorities; reviewed in Naff and Kellough (2003). Other research indicates that reducing the saliency of group identity helps to reduce backlash by majority groups; reviewed in Gilbert et al. (1999), ibid; Bendick et al. (1998), ibid. It should be noted in this context that those programs shown to be effective at increasing the retention of women faculty are almost immediately broadened to include all faculty (Box 6-3).    gF Dobbin and A Kalev (2006). Diversity management and managerial diversity: Addendum to “Best Practices or Best Guesses.” Special Report to the National Academies Committee on Women in Academic Science and Engineering.    hRJ Ely and DA Thomas (2001). Cultural diversity at work: The effects of diversity perspectives on work group processes and outcomes. Administrative Science Quarterly 46:202-228.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering EXPERIMENTS AND STRATEGIES BOX 4-8 Specific Steps for Overcoming Bias Avoid language that activates unexamined and implicit biases (Box 2-4). Make positive role models visible (see Boxes 2-4 and 4-2). Include women and minority-group members on evaluation committees (Box 4-2). Create an enhanced sense of community and partnership (Box 5-2). Discuss possible bias and challenge decisions openly (Box 4-4). Make the community aware of the research on bias and emphasize the neutral effect of the gender of the evaluator, thereby defusing the issue and avoiding accusations and defensiveness (Box 4-9). Define criteria at the outset of the selection process to ensure that they select the best academic traits rather than simply replicating past patterns (Boxes 4-1, 4-6, and 4-7). Hold accountable people and committees that conduct evaluations of people for hiring, tenure, promotion, and awards (Boxes 4-2, 4-6, and 4-7). FOCUS ON RESEARCH BOX 4-9 Top Research Articles on the Effects of Bias on Evaluationa Each of the 19 institutions that have received NSF ADVANCE grants were asked which research publications have proven most effective in their institutional transformation projects. The most-cited publications were these: RE Steinpreis, KS Anders, and D Ritzke (1999). The impact of gender on the review of the curricula vitae of job applicants and tenure candidates: A national empirical study. Sex Roles: A Journal of Research 41:509-528. F Trix and C Psenka (2003). Exploring the color of glass: Letters of recommendation for female and male medical faculty. Discourse and Society 14(2):191-220. V Valian (1999). Why So Slow: The Advancement of Women. Cambridge: MIT Press. C Wennerås and A Wold (1997). Nepotism and sexism in peer-review. Nature 387: 341-343.    aAll 19 ADVANCE institutions were polled on the top 3-5 articles that have proven the most effective in their institutional transformation projects. Poll conducted between January 20 and March 20, 2006.

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Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering The committee has prepared a detailed scorecard for the purposes of measuring progress toward improving the representation of women in university programs and faculties (Box 6-7). Measurables include Changes in the representation of women and minorities in the student body, new faculty interviews, hire offers, faculty rank positions, and in administrative positions. Changes in hiring, promotion, tenure, retention, and turnover. Exit interviews can be an important means of evaluating reasons for turnover and designing retention programs (Box 3-5). Differences in salary or resource allocation. BEYOND BIAS The underrepresentation of women and minorities in science and engineering faculties stems from a number of issues that are firmly rooted in our society’s traditions and culture. To accelerate the rate at which women and minority-group members take their places as leaders in science and engineering, it is essential that all members of the scientific and engineering community—men and women alike—reflect on their own values, beliefs, and behavior to ensure that they do not further stereotypes, prejudices, policies, practices, or climates that discourage or exclude women and minorities from academe (Box 4-8). A powerful way to reduce evaluation bias has been to bring to the attention of those performing evaluations—including provosts, department chairs, and search committees—the research in the field (Box 4-9). CONCLUSION Our analysis shows that women possess the qualities needed to succeed in academic careers and can do so when given an equal opportunity to achieve. Furthermore, reducing the homogeneity of faculty enhances problem solving, teaching, and research. The need to eliminate bias against women scientists and engineers—whether explicit, covert, or unexamined— is therefore more than a moral or legal obligation of universities. It is a requirement for assuring a scientific workforce of the highest quality. Only the best possible scientific workforce will permit the nation to compete in an increasingly global world of science and engineering.