What John Tierney Gets Wrong About Women Scientists
Understanding a new study about discrimination.
Ceci and Williams did not show, or claim to show, that there was no discrimination or unconscious bias against women scientists. Instead, they tried to untangle the complicated causal factors that influence success. 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. But if you compare male and female scientists with identical resources you find that the women are just as likely to be successful. 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 in the study I described before. It's much more likely that gender causes the unequal resources, which causes the different outcomes
How can you reconcile the experimental résumé studies with the fact that women with as many resources as men have their papers, grants, and job applications accepted at equal rates? There are lots of possibilities. Women, knowing that they are subject to discrimination, may work twice as hard to produce high-quality grants and papers, so that the high quality offsets the influence of discrimination, just like HDL and LDL cholesterol. Even more likely, the kind of conscious efforts to overcome bias that Tierney dismisses may actually be working, thus offsetting unconscious discrimination.
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 that leads from graduate school to first job and beyond. They often settle in jobs at lower tier schools with fewer resources and fail to even apply for publications, grants, or the best jobs at the best universities. Perhaps these women are simply choosing to have fewer resources. Or perhaps they want to have children. 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?
This tension between experimental studies and correlational ones is not uncommon in science, but the rule is that experiments win. In this case, the experiments prove that there is bias against women—and the correlational data suggest that this bias interacts with other factors in complicated ways to influence their success. 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.
Photograph by Stockbyte/Thinkstock.