SMART NEWS

If Women Assume Fake Names, They Do Better on Math Tests

Assuming a false name helped women perform better on math tests

Contributor

July 3, 2013

There’s a long standing myth that men are better at math than women. Women know this myth, and if you remind them of it before a test, they tend to do worse than they would have otherwsie. This is called “stereotype threat,” and it happens in the real world all the time. One team of researchers was interested in whether or not they could reverse this drop in performance by having women assume fake identities. What they found was that assuming a false name did help women perform better.

Here’s how the study, excellently titled “L’eggo My Ego: Reducing the Gender Gap in Math by Unlinking the Self from Performance,” worked, according to Research Digest:

Shen Zhang and her team tested 110 women and 72 men (all were undergrads) on 30 multiple-choice maths questions. To ramp up the stereotype threat, the participants were told that men usually outperform women on maths performance. Crucially, some of the participants completed the test after writing their own name at the top of the test paper, whereas the others completed the test under one of four aliases (Jacob Tyler, Scott Lyons, Jessica Peterson, or Kaitlyn Woods). For the latter group, the alias was pre-printed on the first test page, and the participants wrote it on the top of the remainder.

The authors of the study made a distinction between two different kinds of stereotype threat. There is group-reputation threat—where women fear doing poorly because they worry it will reflect badly on women in general. And there is self-reputation threat—where women fear doing poorly because they worry it will be taken as proof of a stereotype (in this case, that women are bad at math).

Here’s what happened when the researchers gave women fake names. Women who took the test under a false name—male or female—performed significantly better than women who took the test with their own name at the top. Men were completely unaffected by the name on the top of their paper. The authors of the paper explain that their results suggest that “concerns about self-reputation are a prominent component of stereotype threat among a general sample of women in math, and largely drive women’s underperformance in situations that cue gender stereotypes.” Their results, they writes “speak to the benefits of using non-name identification procedures in testing. But more generally, they suggest that coping strategies that allow stigmatized individuals to disconnect their self from a threatening situation can be an effective tool to disarm negative stereotypes.”