Department of Human Development, Cornell University, Ithaca, NY 14853, USA.
Proc Natl Acad Sci U S A. 2011 Feb 22;108(8):3157-62. doi: 10.1073/pnas.1014871108. Epub 2011 Feb 7.
Explanations for women's underrepresentation in math-intensive fields of science often focus on sex discrimination in grant and manuscript reviewing, interviewing, and hiring. Claims that women scientists suffer discrimination in these arenas rest on a set of studies undergirding policies and programs aimed at remediation. More recent and robust empiricism, however, fails to support assertions of discrimination in these domains. To better understand women's underrepresentation in math-intensive fields and its causes, we reprise claims of discrimination and their evidentiary bases. Based on a review of the past 20 y of data, we suggest that some of these claims are no longer valid and, if uncritically accepted as current causes of women's lack of progress, can delay or prevent understanding of contemporary determinants of women's underrepresentation. We conclude that differential gendered outcomes in the real world result from differences in resources attributable to choices, whether free or constrained, and that such choices could be influenced and better informed through education if resources were so directed. Thus, the ongoing focus on sex discrimination in reviewing, interviewing, and hiring represents costly, misplaced effort: Society is engaged in the present in solving problems of the past, rather than in addressing meaningful limitations deterring women's participation in science, technology, engineering, and mathematics careers today. Addressing today's causes of underrepresentation requires focusing on education and policy changes that will make institutions responsive to differing biological realities of the sexes. Finally, we suggest potential avenues of intervention to increase gender fairness that accord with current, as opposed to historical, findings.
女性在数学密集型科学领域代表性不足的原因通常集中在资助、稿件评审、面试和招聘过程中的性别歧视。女性科学家在这些领域受到歧视的说法基于一系列旨在补救的政策和计划的研究。然而，最近更有力的实证研究并不能支持这些领域存在歧视的说法。为了更好地理解女性在数学密集型领域代表性不足的问题及其原因，我们重新审视了歧视的说法及其证据基础。基于对过去 20 年数据的回顾，我们认为其中一些说法已经不再成立，如果不加批判地将其视为女性缺乏进步的当前原因，可能会延迟或阻碍对当代女性代表性不足的决定因素的理解。我们得出结论，现实世界中不同性别结果的产生是由于资源差异所致，而这些资源差异可以归因于选择，无论是自由选择还是受限制的选择。如果资源得到合理配置，这些选择可以通过教育来影响和更好地指导。因此，目前对评审、面试和招聘过程中的性别歧视的关注是代价高昂且错误的：社会正在解决过去的问题，而不是解决当前阻碍女性参与科学、技术、工程和数学职业的有意义的限制因素。要解决当前代表性不足的问题，需要关注教育和政策改革，使机构能够对性别差异的生物学现实做出反应。最后，我们提出了一些潜在的干预途径，可以增加性别公平，这些途径符合当前的发现，而不是历史上的发现。
