Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering The National Academies

1. Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering The National Academies September 18, 2006

2. Beyond Bias and Barriers, NAS Committee • DONNA E. SHALALA(Chair), President, University of Miami • ALICE M. AGOGINO, University of California, Berkeley, California • LOTTE BAILYN, Massachusetts Institute of Technology, • ROBERT J. BIRGENEAU Chancellor, UC, Berkeley, • ANA MARI CAUCE, Executive Vice Provost University of Washington • CATHERINE D. DEANGELIS Editor-in-Chief, JAMA • DENICE DENTON*, Chancellor, UC, Santa Cruz, California • BARBARA GROSZ, Harvard University, Cambridge, Massachusetts • JO HANDELSMAN, HHMI Professor, University of Wisconsin, Madison, • NAN KEOHANE, President Emerita, Duke University, • SHIRLEY MALCOM AAAS • GERALDINE RICHMOND, University of Oregon • ALICE M. RIVLIN Brookings Institution, Washington, DC • RUTH SIMMONS President, Brown University • ELIZABETH SPELKE Harvard University • JOAN STEITZ HHMI, Yale University School of Medicine, • ELAINE WEYUKER AT&T Laboratories • MARIA T. ZUBER Massachusetts Institute of Technology

4. More women are earning science and engineering doctorates

5. But women are leaving academic careers Increasing the number of women earning science and engineering doctorates will have little effect on the number of women in academic positions, unless attention is paid to recruiting women to these positions and retaining them once hired.

6. FINDINGS

7. FINDINGS • Differences in biology and aptitude • Pipeline • Outright discrimination • Unconscious bias • Climate • Rules, policies, and structures

8. Research on: • brain structure and function • hormonal modulation of performance • cognitive development • performance in math and science • no significant biological differences between men and women that would explain representation • no significant differences in performance in science and math that account for representation • representation of women has increased 30-fold in some fields in the last two decades, which shows that when opportunities in science are available women, they take them and excel Women have the drive and ability to succeed in science and engineering.

9. Women who are interested in science and engineering careers are lost at every educational transition. • high school to college • college to graduate school • doctorate to tenure-track positions • active recruiting, mentoring, and changes in the system can alter this

10. For more than 30 years, women have comprised 20 to 45% of the life sciences Ph.D. pool • But at top research institutions, women comprise • <15% of full professors in the life sciences • minority women are virtually absent from leading science and engineering departments The problem is not simply the pipeline --

11. FINDINGS • Differences in biology and aptitude • Pipeline • Outright discrimination • Unconscious bias • Climate • Rules, policies, and structures

12. Barriers limit the appointment, retention, and advancement of women faculty • Female and minority scientists and engineers have had to function in environments that favor white men • Minority women are subject to dual discrimination and face even more barriers • All women scientists face continuous questioning of their abilities and commitment Women are very likely to face discrimination in every field of science and engineering.

13. Women are very likely to face discrimination in every field of science and engineering. • Women must pursue their careers without the opportunities and encouragement provided to white men • Accumulation of disadvantage becomes acute in more senior positions

14. A substantial body of evidence establishes that most people—men and women—hold implicit biases. • Decades of cognitive psychology research shows that • most of us intend to be fair • most of us carry unconscious prejudices • these biases influence our evaluations of people and their work

15. What does the research say about bias and prejudice? • Blind, randomized trials • Real life studies

16. Hiring Evaluators review credentials of applicant • Substantially more likely to hire the person if there is a man’s name on application • More likely to hire if a “masculine” scent put on the materials than if “feminine” scent

17. Research on Bias Meta-analysis of studies of hiring • Aggregate of 1,842 subjects over 19 studies • Applications assigned male or female name • Reviewers hired male candidates more often (Olian et al., 1988) Review of description of job performance • Rated the same job performance lower if told it was performed by a woman (Dovidio and Gaertner, 2000) Difference was substantially greater when evaluator was busy or distracted (Martell, 1991)

18. Research on Bias Ability rated as primary cause of success Attractive male 50% Unattractive male 34% Attractive female 28% Unattractive female 62% Heilman, 1985 Success of attractive women more often attributed to luck (Heilman, 1985; Deaux and Emswiller, 1974)

19. After-the-fact Explanation for Biased Choices • Hiring study – who would you hire and why? • Result – more likely to hire whichever application had man’s name on it • Why – whichever trait in which the man is stronger (education or experience)

20. Research on Bias • In every study, significant effect of gender or race of person evaluated • NO significant effect of gender or race of person doing the evaluation

21. What does the research say? • Blind, randomized trials • Real life studies

22. Swedish Postdoc Fellowship Study • Compared “competency rating” with “publication impact rating”

23. Swedish Postdoc Fellowship Study Wenneras and Wold, 1997. Nature 387:341.

24. Research on Bias • CVs of real woman assigned a male or female name, randomly, and sent to 238 academic psychologists • CV at time of job application • CV at time of early tenure decision • Respondents more likely to hire if male name • Gender of applicant had no effect on respondents’ likelihood of granting tenure Steinpreis et al., 1999

25. Research on Bias There were “cautionary comments” in margins of tenure package four times more often on those with woman’s name: “We would have to see her job talk.” “It is impossible to make such a judgment without teaching evaluations.” “I would need to see evidence that she had gotten those grants and publications on her own.” Steinpreis et al., 1999

26. Stereotype Threat….. ….is people living up or down to a stereotype of their “group” • Activated by reminder of their gender or race • If Asian women are reminded of their ethnicity before taking a math test, they perform better • If reminded of their gender, they perform worse

27. Stereotype Threat….. ….is people living up or down to a stereotype of their “group” • If told that a study is about “how people solve problems” girls will do as well as boys • If told that the study is “to evaluate the math abilities of boys and girls,” girls’ performance is lower than boys’

28. FINDINGS • Differences in biology and aptitude • Pipeline • Outright discrimination • Unconscious bias • Climate • Rules, policies, and structures

29. Measures of success underlying the current “meritocracy” • are often arbitrary • are applied in a biased manner • do not necessarily relate to scientific creativity • celebrate assertiveness and single- mindedness (typically male) • do not celebrate flexibility, diplomacy, curiosity, motivation, and dedication (more typically female) • penalize women for assertiveness and single-mindedness

30. Academic structures and rules contribute significantly to the underutilization of women in academic science and engineering. • Rules that appear neutral have differential effects on men and women • Structural constraints and expectations based on assumption that faculty membershave spousal support • However, most spouses of faculty in science and engineering are employed full-time (90% of husbands, ~50% of wives)

31. RECOMMENDATIONS

32. RECOMMENDATIONS • University leaders • Deans and department chairs • Faculty • Congress • Professional societies • Federal agencies

33. Trustees, university presidents, and provosts University leaders should hold leadership workshops for those with personnel management responsibilities • include an integrated component on diversity • Include strategies to overcome bias • include strategies for encouraging fair treatment of all people LEADERSHIP WORKSHOPS

34. Trustees, university presidents, and provosts University leaders should • require evidence of a fair, broad, and aggressive search • hold departments accountable for the outcomes even if it means canceling a search or withholding a faculty position. FACULTY RECRUITMENT

35. Trustees, university presidents, and provosts Policies that take into account human needs across the life course, allowing integration of family, work, and community responsibilities. • funding for family leave • help with children or other care-giving responsibilities to maintain productive careers • on-site and community-based child care • dissertation defense and tenure clock extensions • family-friendly scheduling of critical meetings HIRING, TENURE, and PROMOTION POLICIES

36. Deans, department chairs, and tenured faculty Educate all faculty members and students about unexamined bias and effective evaluation. • integrate into departmental meetings and retreats, and professional development and teacher-training courses. • incorporate into research ethics and laboratory management courses for graduate students, postdoctoral scholars EVALUATION

37. Higher education organizations, scientific and professional societies, journals, and honorary societies have a responsibility toplay a leading role in promoting equal treatment of women and men and demonstrate this commitment in their practices.

38. Higher education organizations Together, higher education organizations should consider forming aninter-institution monitoring organization. • act as an intermediary between academic institutions and federal agencies • recommend norms and measures, in collecting data, and in cross-institution tracking of compliance and accountability • the American Council on Education should convene national higher education organizations to consider the creation of a monitoring body EVALUATE and MONITOR

39. Set professional and equity standards • Collect and disseminate field-wide education and workforce data • Provide professional development training for members that includes a component on bias in evaluation • Provide child care at national meeting • Ensure representation and visibility of women as speakers, on editorial boards, and as recipients of society awards Scientific and professional societies EVALUATE and MONITOR

40. Federal funding agencies: ensure that practices support the full participation of women and do not reinforce a culture that fundamentally discriminates against women

41. Examples of Actions • Consider blind reviews • Study sources of bias • Review language in all RFPs for bias • Halt mid-process review processes that discriminate against women • Use images of famous women and minorities • Educate panels, reviewers, and panel managers about unconscious bias, use criteria constructed before review and tell them not to be prejudiced

42. Federal funding agencies: • enforce existing anti-discrimination laws • use “equity scorecard” in NAS report to evaluate universities for advancement of women in science • include campus rating in training grant applications • require equity training for all PIs and trainees

43. Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering The National Academies September 18, 2006