Debunking Discrimination
A blunt article in PNAS by Ceci and Williams provides considerable evidence that the underrepresentation of women in mathematically intensive fields is not due to systematic discrimination:
Women’s current underrepresentation in math-intensive fields is not caused by discrimination in these domains, but rather to sex differences in resources, abilities, and choices (whether free or constrained). Thus, current initiatives direct energy toward solving past problems rather than current ones. Women’s underrepresentation today results from a complex set of interrelated factors, some of which society could meaningfully address if the focus was placed squarely on them. One key to such success is moving beyond historical issues and confronting current ones.
The paper systematically examines the evidence for gender discrimination in grant and publication acceptance rates and in hiring, and finds it lacking. The story is consistent: for almost every paper discussed that provides evidence of discrimination, subsequent papers that do more rigorous analyses find no effect. (The authors do acknowledge that discrimination does occur, but that discrimination is the exception rather than the rule)
the evidence shows women fare as well as men in hiring, funding, and publishing (given comparable resources)
The key is the "given comparable resources" part - the authors note that women tend to be particularly poorly represented in research intensive positions that would give them the time and resources needed to publish more / produce more grants.
The explanation for the differing resource availability?
That women tend to occupy positions offering fewer resources is not due to women being bypassed in interviewing and hiring or being denied grants and journal publications because of their sex. It is due primarily to factors surrounding family formation and childrearing, gendered expectations, lifestyle choices, and career preferences—some originating before or during adolescence - and secondarily to sex differences at the extreme right tail of mathematics performance on tests used as gateways to graduate school admission.
Pretty much in line with Larry Summers' talk, and there are lots of footnotes. (Today's Times, by the way, has an interesting discussion of the Summers brouhaha.)
One thing that was new to me was a study of gender differences in career preferences:
adolescent girls often prefer careers focusing on people as opposed to things, and this preference accounts for their burgeoning numbers in such fields as medicine and biology, and their smaller presence in math-intensive fields such as computer science, physics, engineering, chemistry, and mathematics, even when math ability is equated. In a recent metaanalysis of >500,000 participants, the male-female effect size for preferring people vs. things overall was d > 0.90, and for engineering, 1.1, both substantial differences.
The authors aren't saying that the differing numbers of women in mathematical sciences is not a problem because it is a chosen situation. They emphasize:
To the extent that women’s choices are freely made and women are satisfied with the outcomes, then we have no problem. However, to the extent that these choices are constrained by biology and/or society, and women are dissatisfied with the outcomes, or women’s talent is not actualized, then we most emphatically have a problem. With a redirection of resources, this problem might be addressed by education and outreach to young women and girls and to academic administrators. Past strategies to remediate women’s underrepresentation can be viewed as a success story; however, continuing to advocate strategies successful in the past to combat shortages of women in math-based fields today.
The paper suggests some promising strategies for addressing remaining barriers to greater participation of women in math-intensive fields. One in particular is programs like Berkeley's "Family Friendly Edge"
Definitely a paper worth reading of the issue of women in science is of interest.
-
on Mon, Feb 28, 10:02PM
What is "systematic discrimination" and is it supposed to be different from "overt discrimination"?
Some detailed comments about flaws in the PNAS article are here. For starters, the statistics in the first paragraph that are labeled "tenure track" should be labeled "all ranks."
Some limitations of the study on gender differences in career preferences: This was a survey that collected responses to interest inventories. The connection between responses to interest inventories and choice of vocation appears to be unknown. The authors (Su et al.) note that validity studies conducted in the 1970s lead to “a variety of conclusions depending on how percentage agreement between interest score and criterion was assessed” (p. 861). These studies focused on only a few types of surveys, thus, as Su et al. note, their results had limited generalizability.
Su et al. note that the proportions of men and women showing interest in engineering via survey responses are similar to those actually employed in engineering. However, this is not the case for science and mathematics. They say: "This discrepancy between interest data and real employment composition indicates that there may be reasons other than sex differences in interests that can account for gender disparity in science and mathematics."
