Gender Bias

Pulled from a Slate article. Discuss.

This matters because, whatever the influence of genetics may turn out to be, there is no doubt that the enduring social consensus that women are on average worse than men in math and science plays a major role in shaping women's careers and their career choices. It does so in two ways: through discrimination and through socialization. Contrary to the pie-in-the-sky assumptions of many of Summers' media defenders, studies show that discrimination against women in the academy is alarmingly widespread, if often unconscious. M.A. Paludi and W.D. Bauer conducted a study in which 180 men and 180 women were asked to grade a paper on a five-point scale. When the author was "John T. McKay" rather than "Joan T. McKay," the men on average graded the paper a point higher—and the women scoring the test weren't much more egalitarian. And studies have shown that men writing mathematics papers are less likely to cite women than women are (1.2 percent of the time, compared to 4.8 percent)*. Scientists and engineers may say they aren't biased. But consider the case of classical musicians: Until blind auditions were held for national orchestras, women were radically underrepresented in field of classical music. Many argued that women had less wind power and were biologically incapable of performance at highest levels on many instruments. Since blind auditions have been held, though, the participation of women has risen precipitously—evidence that it was almost entirely discrimination that was keeping women out.

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Steele studies the way stereotypes affect people's performance. And he has found that when women are told that a test is going to measure cognitive differences between genders they tend to do much worse than men. But when they're told a test is gender-blind, they tend to perform as well. The pressure of the "stereotype threat," as Steel terms it, actually leads women to do worse, in other words. The amazing thing is, as Steele convincingly argues, stereotype threat most affects those at the high end of the spectrum in math and science, because they're the ones who are the most identified with the field and have the most to lose as they move upward and are increasingly identified as, say, a "female engineer." This doesn't mean that men aren't outperforming women at the very high end of the bell curve, as my colleague Will Saletan points out; but it makes it look as though socialization is a weighty factor in gender disparities at top levels.