There Is a Gender Bias When It Comes to Hiring Men and Women Who Are Good at Math

The economist Larry Summers famously suggested once that so few women become scientists and engineers because of discrimination, preference and even differences in innate ability.

In a paper published Monday in the Proceedings from the National Academy of Sciences, three business school professors tried to isolate the first of those reasons. They set up a lab experiment in which “managers” hired people to complete mathematical tasks that, on average, men and women performed equally well.

With no information about the job “applicants” other than their appearance, the managers (of both sexes) were twice as likely to hire a man over a woman.

In Economix, Shaila Dewan looks at a study showing that women who can do math often don’t get hired because of discrimination bias. Women have a tendency to downplay their abilities while men have a tendency to “boast,” but even when managers were given hard data about the applicants’ abilities to perform tasks, “Managers were still one-and-a-half times more likely to hire a man. When they knowingly chose the lower-performing candidate, two-thirds of the time they were choosing the male applicant.”

So how can they correct this? Managers were given an “implicit association test,” or I.A.T., to measure their gender bias when it comes to math and science.

“Anyone can do an I.A.T., and if they know that they are biased they should correct for that,” one of the professors of the study said.

Photo: Jeremy Piccola

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