We All Know That Anything a Man Can Do, a Woman Can Do Just as Well, Right?

Blackburn and Greider

How stereotypes impair women's careers in science

Elizabeth Blackburn (left) and Carol Greider (Photo credit: Gerbil, Licensed by Attribution Share Alike 3.0). Winners of 2009 Nobel Prize in Physiology or Medicine

Significance

Does discrimination contribute to the low percentage of women in mathematics and science careers? We designed an experiment to isolate discrimination’s potential effect. Without provision of information about candidates other than their appearance, men are twice more likely to be hired for a mathematical task than women. If ability is self-reported, women still are discriminated against, because employers do not fully account for men’s tendency to boast about performance. Providing full information about candidates’ past performance reduces discrimination but does not eliminate it. We show that implicit stereotypes (as measured by the Implicit Association Test) predict not only the initial bias in beliefs but also the suboptimal updating of gender-related expectations when performance-related information comes from the subjects themselves.

Author contributions: E.R., P.S., and L.Z. designed research; E.R. performed research; E.R., P.S., and L.Z. analyzed data; and E.R., P.S., and L.Z. wrote the paper.

— From the Proceedings of the National Academy of Sciences

Here in 21st century America, we all know that anything a man can do, a woman can do just as well, right? Well it turns out when it comes to math and science, we don’t all know that, and this bias could be costing women valuable career opportunities.

The latest research from Luigi Zingales from the University of Chicago Booth School of Business, published March 10 in the Proceedings of the National Academy of Science’s Early Edition, demonstrates that both men and women are biased against women when it comes to hiring for math-related work.

In "How Stereotypes Impair Women's Careers in Science," Zingales, along with Ernesto Reuben of Columbia Business School and Paola Sapienza of the Kellogg School of Management at Northwestern University, ran a laboratory experiment to measure how employers respond to female applicants when hiring for a job that involves arithmetic. They found that when presented with no additional information about candidates, other than their genders, that both sexes are twice as likely to hire a man as a woman.

Even when the interviewees had the chance to tell the employers about how well they expected to do on an upcoming arithmetic test, the economists found that the bias remained in place because men tend to boast and to inflate their abilities, which the hirers were willing to believe. As the same time, they found that women tend to underestimate their abilities.

When candidates were considered alongside results from a completed arithmetic test, the bias against women lessened, but still did not go away. As a result, regardless of the situation, the decision to hire less-qualified male candidates over well-qualified female candidates remained commonplace. Taking the results out of the laboratory and into the real world, this means that women are losing the chances to join STEM career paths and that employers are not always hiring the best workers.

Zingales and his colleague's findings also suggest that both sexes discriminate against women without realizing that they do so, which means that different, new policies are needed to remedy the situation.

From the University of Chicago

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We All Know That Anything a Man Can Do, a Woman Can Do Just as Well, Right?

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