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Dr. Urry is the Israel Munson Professor of Physics and Astronomy, Director of the Yale Center for Astronomy and Astrophysics and Chair of the Department of Physics at Yale University.
Everyone agrees there are too few women and minorities in science. As a graduate student, postdoc, young faculty member, and now tenured senior scientist, I have repeatedly seen women colleagues being undervalued or overlooked. But it wasn't until I became familiar with the social science literature that I could fit a viable theory to my experience. In particular, my eyes were opened by Virginia Valian's influential book summarizing this research, "Why So Slow? The Advancement of Women" (Valian 1999). Here I describe, much as she does, social science experiments that illuminate how present-day society projects its unconscious biases into the workplace. But first, a few words about why this issue is so important.
Many scientists believe that increasing diversity is a matter of social engineering, done for the greater good of society, but requiring a lowering of standards and thus conflicting with excellence. Others understand that there are deep reasons for the dearth of women (discussed below) wholly unrelated to the intrinsic abilities of women scientists which lead to extra obstacles to their success. Once one understands the bias against women in male-dominated fields, one must conclude that diversity in fact enhances excellence. In other words, the playing field is not level, so we have been dipping more deeply into the pool of men than of women, and thus have been unknowingly lowering our standards. Returning to a level playing field (compensating for bias) will therefore raise standards and improve our field. Diversity and excellence are fully aligned.
What Data Show
Hundreds of studies across many fields demonstrate that the advancement of women lags that of men with the same qualifications. Using NSF data for a synthetic cohort corrected for time since degree, type of institution, specialty, and family status, Long (2001) reviewed the gender dependence of salary, rank and tenure in science and engineering, Women lag behind, in advancing and in getting tenure. Having children has the effect of removing women from the full-time workforce, but differences for women who remain in full-time positions are minimal (Mason and Goulden 2002).
Why Are Women Scarce in Science?
Some of my colleagues believe women are simply not interested in science (at least, not in the physical sciences) and the loss of talent does not seem to worry them. Yet Xie & Shauman (2003) showed that interest in the sciences does not correlate with ability. Furthermore, they found that sex disparities in productivity (e.g., publication rates) were decreasing, and that productivity depends most strongly on access to resources and is independent of family status. And countries with excellent maternity and childcare benefits (e.g., Nordic countries) have some of the lowest participation of women in Physics. Women with families do participate in extremely demanding careers such as medicine.
If it is not ability or interest, what is it? There is plenty of evidence that the playing field is not level for women and men. In 1997 Wenneras and Wold published a study in Nature about applications for a prestigious Swedish postdoctoral fellowship in medicine. They showed that although 46% of the applications were from women, only 20% of the fellowships were awarded to women. Reviewers of the proposals consistently gave women lower scores for the same level of productivity, and women applicants' scores had to be 2.5 times those of men to succeed. A recent study by Budden et al. (2008) showed that the fraction of papers having a woman as first author increased significantly when a biology journal went to double-blind refereeing. While some have suggested women lack innate ability—i.e., women are simply not as good at science as men—this suggestion is contradicted by almost all available evidence. Gender gaps in performance (for example, on math exams) are decreasing in the U.S.; if they were due to physiology, they should not change dramatically on time scales of decades. Moreover, gender gaps vary enormously by country, arguing against a genetic origin. For example, Japanese women score better in math than U.S. men. (See Chapter 2 of the National Academy's Beyond Bias and Barriers report [Shalala et al. 2006].)
At the same time, gender gaps can be explained by culture. Research into "stereotype threat" shows that culture affects test results. For example, a class is told they will be given a difficult math test. Men do poorly, scoring 25 of a possible 100, and women do worse, with an average grade of 10 (Steele 1997, Spencer et. al. 1999). This is the kind of gender gap that makes a front-page page New York Times story: that at the extremes of performance, men substantially outscore women. However, another class is told the same story about a difficult math test, with the added information that the test has been designed to be "gender neutral." Now the women's score doubles to 20 while the average men's score decreases to 20. In other words, men and women score the same. When the stereotype threat is activated, people under stress conform to it.
We are a biased society. It is not overt; most of us think we are unbiased and try hard to be so. It is not only men discriminating against women; it is all of us discriminating against women and minorities (in white-male-dominated fields.) There is evidence that we discriminate against men seeking to join female-dominated fields, like nursing. Valian describes the origin of this bias with "gender schemas," a set of expectations of women and of men, embedded in our culture, that influence how women and men are judged. A large body of research describes the effect of gender schemas; here I give but a few examples:
Heights of men and women (Biernat, Manis & Nelson 1991) Subjects are asked to estimate an objective quantity, namely the heights of men and women in photographs, all of which include some object like a doorway or desk to offer scale. Even though the subjects were chosen so that each gender has the same height distribution, the average height estimated for men is greater than that estimated for the women. We expect men to be taller (indeed, it is true at present in our society as a whole) and so this is what we measure, even when it is not true in the particular data set.
Leader at table (Porter & Geis 1981) Undergraduate students are shown photographs of people sitting around a table and asked to identify the leader. Where all the people pictured are men, the leader is nearly always identified as the person at the head of the table. The same is true when only women are pictured. When both men and women are pictured and a man sits at the head, he is identified as the leader. However, in the mixed gender case with a woman at the head, half the time a random man is identified as the leader.
Eye gaze (Dovidio et al. 1988) First the experimenters establish that in a conversation between a superior and a subordinate (same gender), the superior looks at the subordinate while talking, but looks away when listening. The subordinate spends roughly equal amounts of time looking at and away from the superior, regardless of who is speaking. Then the experimenters showed that in conversations between men and women, men look primarily while talking and women look while both talking and listening, regardless of who is the superior and who is the subordinate. This reinforces the assumption that the man is more powerful than the woman. (Note to women: make eye contact while talking!)
Rating managers (Heilman et al. 2004) Subjects are asked to rate two assistant vice-presidents in a fictitious (but heavily documented) aircraft company (a "male" environment). Men are rated higher than women, despite randomized resumes, but both are deemed likeable. In a second experiment, in which women are validated prior to the evaluation (e.g., subjects are told "both managers have been rated outstanding"), then men and women are rated equally competent but the woman is not likeable and is judged hostile or difficult. That is, women can be competent or likeable but not both.
Gender bias can play an important role in evaluation. For example, letters of recommendation and personal nominations are enormously important for academics in hiring, promotion, invitations to speak, fellowships, grants, and other honors and awards. Yet there are systematic differences in the letters of recommendation for women and for men, as shown, for example, in a study of applications for medical fellowships by Trix & Penska 2003). This is not widely known among science and engineering faculties. Letters for women are shorter and contain fewer standout words ( "outstanding," "ground-breaking," "superstar") and express more doubt and contain more "grindstone" adjectives such as "works hard" and "diligent." They are more likely to mention women's personal lives and, in most cases, the mention of gender is explicit. Women are more likely to be compared to other women (a sure sign that this process is not gender blind). In my own experience, women get asked to write tenure letters for women more often, and their letters are more likely to be discounted or ignored unless they are negative, in which case they are given extra weight. The presence of only a few women guarantees that bias will kick in. In studies of hiring practices, with artificial and matched resumes (Heilman 1980), it was found that women can succeed when they are more than 30% of the applicant pool, whereas they are unlikely to succeed when less than 25%. This has obvious ramifications for job searches or tenure letters that include only one woman as a token on the short list.
This has been a very brief review of what is known from the sociology and psychology research, but enough, I hope, to show that this is not a mysterious problem. Rather, it is a well-understood and tractable problem. There are known remedies. But the first, critical step is to recognize the uneven playing field. Only then can we compensate fairly, and thus have truly objective evaluation of quality.
Gender schemas resist change but also follow change. Change requires education, action, and further research. The first step toward change is to educate our colleagues about the impact of gender on evaluation and career progress. The National Academy of Science's Beyond Bias and Barriers 20 ″ July 2009 PHYSICS AND SOCIETY, Vol. 38, No.3 study summarizes the relevant research and interventions. Many NSF ADVANCE projects have online resources, and universities can develop effective methods to teach scientists the (social) scientific literature (ADVANCE is an NSF program intended to transform academic institutions with respect to women in science; 19 institutions and consortia have been awarded ADVANCE grants; the website of the ADVANCE program is http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5383. Valian maintains a very useful annotated bibliography of relevant research at http://www.hunter.cuny.edu/genderequity/equityMaterials/Feb2008/annobib.pdf.
To make progress, leaders must lead. Most leaders in our field (today) are men. Men therefore have to play a key role in advancing progress of women in science. Leaders must be held accountable for developing excellent staffs, which we argue cannot be excellent if they are not gender balanced. What kind of action can leaders take? First, establish norms. Make sure that colloquia, meetings, prizes, job interviews, etc., involve the appropriate fraction of women. Be articulate in explaining this issue and hold others accountable for their performance. Arrange for training and education. "Pre-validate" women in your organization. Brown and Geis (1984) showed that differential expectations by gender can be minimized if leaders establish women's credentials (see also Heilman et al. 2004). For example, a woman speaker should be introduced with a thorough review of her accomplishments, in order to establish without doubt her expertise. A woman promoted to a new position can be pre-validated in a similar way, by describing explicitly the reasons for her success. Avoid facile solutions like adding a token woman to every committee. For one thing, women are vastly overworked. Also, successful women may compete with, rather than support, younger women. In their book on affirmative action, Clayton and Crosby (1992) suggested that some successful women avoid advocacy for other women because they are deeply invested in the idea of a gender-blind meritocracy; if evaluations are not objective, their own success is invalidated.
You can educate your colleagues about how to write letters of recommendation (Trix & Penska 2003). You can teach students about teaching evaluations, which are more negative for women faculty (see www.crlt.umich.edu/multiteaching/ gsebibliography.pdf). Information and mentoring are also essential. A mentoring program at the Johns Hopkins Medical Institutions dramatically improved the tenure rate for women assistant professors (Fried et al. 1996), and incidentally, also for men who took part in the program—just one example of what's better for women is often better for men. The APS has an active outreach program in this area; see, for example, their website on "Improving the Climate for Women" at http://www.aps.org/programs/women/sitevisits/index.cfm.
Given the common timing for building careers or building families, it is not surprising that many people assume family issues are the reason for the dearth of women in science. The academic world was not designed for people with family obligations. After all, the European academic system was originally designed for monks. Appropriate accommodations for both men and women (such as on-site childcare, sick child care, elder care, delay of tenure clocks for family obligations, travel support for caregivers helping during professional meetings, etc.) can go a long way toward humanizing the modern workplace. Nonetheless, I argue at least three reasons family issues cannot explain why there are not more women in physics or astronomy. First, women without children who remain full-time in the workplace are not more successful than women without children. (Mason & Goulden 2003 is often cited as showing that women's careers are harmed by having children, but this is because those women are more likely to go to part-time status, which indeed is a negative factor, perhaps wrongly, in their subsequent career advancement) Second, there are many women in other demanding fields, like law and medicine. Third, countries with very strong family support systems, such as the Scandinavian countries, have extremely low numbers of women in physics — just a few percent in 2002. Women in academia often complain about how hard we work and how difficult it is to raise a family under those circumstances. Certainly all of us have pulled "all-nighters" to complete a proposal or have traveled for days or weeks on end to give talks or attend meetings. It is no wonder that young people listen to us and decide they can't reasonably balance career and family. Yet I would argue that academic careers are better than most for this purpose. Our hours are flexible and in many countries salaries are better than the average citizen's, so we have the resources to get help with childcare and household tasks. Having a family is hard, no matter who you are or where you work, but it's much harder if you work at a low-wage job with inflexible hours. We should tell young women that the academic life is great for raising a family: The work is fun (so parents are happy), the rewards are great, and we have a lot of control over our lives. My new mantra: Become a professor, have a family!
Finally, advancing in our profession requires passing through an endless series of selection processes: graduate school admissions, hiring, invited talks, prizes, promotions and tenure. It is unlikely, given our societal biases, that these processes are gender-blind. Each of these selection steps requires two things: finding candidates and evaluating them fairly. It is not sufficient to wait for applications to arrive in the mailbox. A proper job search is just that. One should solicit names from colleagues, use community bulletin boards to find and investigate possible women candidates, and attend lots of talks by junior people. Many a search has turned up outstanding but somehow overlooked scientists. The second step is to evaluate all candidates fairly. This cannot be done by declaring oneself or one's colleagues gender blind. Only those who familiarize themselves with the issues of gender bias are likely to evaluate others objectively. Taking these issues into account and actively promoting the advancement of the talented women scientists we need in the modern world will lead to a stronger, better, healthier, fairer scientific community.
Data illustrate the dearth of women in physics. The theory of gender schemas goes a long way toward explaining why this is a difficult, persistent problem. Good intentions are not enough. The status quo will not repair itself. It will take concerted, conscious action on the part of enlightened leaders. We need to transition from a "fix the woman" strategy, toward a "fix the system" strategy. The main problem is our perception of women being less good than men, when objective review says otherwise. Women are not automatically seen as leaders, or in some cases, even as competent. Yet this can be changed, by external validation by accepted authorities, often men.
What can women do for themselves and others? Gain success outside your institution. Take on highly visible jobs. Gather information on what is needed for success. Find effective mentors and mentor others. Negotiate for the resources you need to succeed. Make allies. Most of all, work to improve the system for other women. The key point is that change toward greater equity and thus a higher level of excellence take positive intervention. It will not happen without action.
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Clayton, S., & Crosby, F. 1992, Justice and Gender Consciousness: Deprivation, Denial, and Affirmative Action, (Ann Arbor: University of Michigan Press).
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Porter, N. & Geis, F.L. 1981, "Women and nonverbal leadership cues: When seeing is not believing," in C. Mayo & K M. Henley (Eds), Gender and nonverbal behavior (Berlin: Springer Verlag), pp. 39-61.
Shalala, D., et al. 2006, "Beyond Bias and Barriers: Fulfilling the Potential of Women in Academic Science and Engineering," (Washington, DC: National Academies Press)
Spencer, S. J., Steele, C. M., & Quinn, D. M. 1999, "Stereotype threat and women's math performance," Journal of Experimental Social Psychology, 35, 4-28.
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Trix, F. & Penska, C. 2003, "Exploring the color of glass: letters of recommendation for female and male medical faculty," Discourse & Society ,14, 191–220.
Valian, V. 1999, Why So Slow? The Advancement of Women (Cambridge: MIT Press). Wenneras, C. & Wold, A. 1997, Nature, 387, 341-343.
Xie, Y. & Shaumann, S. A. 2003, Women in Science: Career Processes and Outcomes (Cambridge: Harvard).
This contribution has not been peer refereed. It represents solely the view(s) of the author(s) and not necessarily the views of APS.