Last year, I criticized universities for hurrying to implement programs to combat microaggressions, “mostly subtle, mostly inadvertent slights directed at racial minorities and other ‘marginalized” groups.’” According to a review of the research conducted by Scott Lilienfeld, professor of psychology at Emory University, there was little, if any, evidence that such programs do more good than harm. Universities, which should pride themselves on following the evidence wherever it leads, seemed to have succumbed to the pressure to “do something” about racism.

One might imagine that this phenomenon is limited to administrators and faculty who don’t understand what the science says. Alas, scientists have proven little better than non-scientists at weighing the evidence, when it comes to politically charged topics like race and gender bias.

For those who want to know more about this problem, I recommend Lee Jussim’s blog, Rabble Rouser. One could accuse Jussim, a professor of psychology at Rutgers University, of prejudice in favor of rabble-rousing, particularly concerning left-wing bias in the sciences. However, he and his colleagues recently provided the first empirical support for a proposition widely believed by psychologists, which holds that inaccurate stereotypes can have a cumulative effect far greater than what we can see in “dyadic” studies involving one perceiver and one perceived.

It is conventional political wisdom on the left that, for example, when teachers inaccurately claim that women are less equipped to excel in college than men, women will underperform as a result. This effect is believed to be observable across a variety of inaccurate stereotypes, particularly about race and sex. It may have been just like rabble rouser Jussim to notice that a widely held left-affirming view lacks empirical support. But it is also just like Jussim to investigate and let the chips fall where they may, or, again, to follow the evidence wherever it leads.

Following the evidence wherever it leads may be damaging to the conventional wisdom that women scientists suffer widely from “implicit bias” when it comes to their prospects for career advancement. There is certainly some evidence for this proposition. A well-known study that presented participants with identical applications for a lab manager position, with only the gender of the applicant varying, found that participants “rated the male applicant as significantly more competent and hirable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant.” There is also evidence from multiple studies, finding bias in favor of women.

As Jussim points out, scientists who cite the first study and fail to acknowledge the existence of the others seem to be biased in favor of the thesis that bias explains disparate outcomes. The American Association for the Advancement of Science (AAAS) held a conference in 2016 in which “presentation after presentation by famous, influential, and prestigious scientists argued for the power and prevalence of implicit gender biases in peer review,” the vetting of a scientist’s grant proposals and paper submissions by other scientists. But “not a shred of evidence of implicit bias in peer review was actually presented” at the conference.

Jussim doesn’t claim that no such evidence exists. But he is distressed that distinguished scientists were presenting as settled science the implicit bias explanation for differences in professional outcomes, even though the evidence for that explanation is, at best, quite mixed. He pointed us to a recent series of studies in which five different political science journals looked for evidence of bias in their peer review processes. Even though “the journals differ in terms of substantive focus, management/ownership, as well [as] editorial structure and process, none found evidence of systematic gender bias in editorial decisions.”

The only bias the speakers at the AAAS demonstrate here is “bias in favor of bias.” Jussim concluded that “this sort of thing is commonplace, when scientists allow their political agendas to drive their claims about science.” This conclusion does not imply that all claims regarding the influence of bias in higher education are false or, more broadly, that the scientific method doesn’t work. It does suggest that scientists who are adept at exposing the foolishness of non-scientists need to attend more closely to their own.

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