It burns, it burns!
What the New York Times' John Tierney gets wrong about bias and women scientists: John Tierney suggested that a "taboo on discussing sex differences" has prevented frank discourse about the real reason why the ratio of male to female scientists is so skewed. He went on to cite a new paper by Stephen Ceci and Wendy Williams... that, he claimed, contradicts the "assumption that female scientists [face] discrimination and various forms of unconscious bias." But, in fact, the paper's authors make a narrower argument, and some of the evidence they present suggests that female scientists almost certainly do face discrimination and various forms of unconscious bias.
Here's what Ceci and Williams show: That women with the same resources as men are just as likely to get their papers, grants, and job applications accepted. While this might appear to mean that women scientists don't face discrimination, in fact, it's quite compatible with the strong experimental evidence that there is bias against women....
[A]s every first year statistics course will tell you, is that correlation does not imply causation. Nicotine-stained fingers are correlated with lung cancer—people with yellow fingers are more likely to have cancer—but yellow fingers don't actually cause cancer. Also, just because you don't find a correlation between two factors, you can't conclude that there is no causal relation between them—it's possible that two causal factors cancel each other out. For example, you might fail to find a correlation between cholesterol and atherosclerosis because you lumped together two different kinds of cholesterol, LDL, which increases the problem, and HDL which decreases it.... [S]uppose you discover that there is a correlation between poverty and ill health, but this correlation disappears when you factor in health care and nutrition. The few poor people with high-quality health care and nutrition are as healthy as rich people—it's just that hardly any poor people have these advantages. It would be wrong to conclude from this that poverty has no causal influence on health. The right conclusion would be that poverty causes bad health care and poor nutrition, which cause ill health.
Ceci and Williams did not show, or claim to show, that there was no discrimination or unconscious bias against women scientists.... They found that when you factor in women's circumstances—for example, what kinds of teaching loads they have, whether they are at research universities, whether they have young children, and so on—then the correlation between sex and success goes away. Overall, female scientists have fewer resources than male scientists, just as poor people have less access to health care.... Ceci and Williams put it this way in their discussion of the number of journal articles women published:
The primary factor affecting women's productivity was structural position. When type of institution, teaching load, funding, and research assistance were factored in, the productivity gap completely disappeared (which is not to say discrimination has not influenced these factors in the real world).
Concluding from this that gender doesn't influence scientific success, however, would be like concluding that poverty doesn't influence health.... It's much more likely that gender causes the unequal resources, which causes the different outcomes....
Why does gender lead to unequal resources? Ceci and Williams accurately paint the big picture. Women drop out in ever greater numbers as they advance along the academic pipeline.... Ceci and Williams cite several studies showing that the conflict between female fertility and the typical tenure process is one important factor in women's access to resources. You could say that universities don't discriminate against women, they just discriminate against people whose fertility declines rapidly after 35.
But as Ceci and Williams admit, the unquestionable fact of unconscious bias, as revealed in the experimental résumé studies, is another possible reason women make choices that lead them to end up with fewer resources. Those studies show that women are subject to bias from the very start of their careers. Is it any wonder that many of them, keenly aware that their efforts are being downgraded compared to those of men, would withdraw from a competition that is systematically unfair?...
Science reporters are supposed to understand these complexities and explain them to their readers—not claim, in spite of the evidence, that sex discrimination is a figment of the biased liberal imagination.