There’s an unfounded gender stereotype that says women aren’t as good at maths as men. Reminding them of this prior to a maths task usually undermines their performance – just one example of a harmful phenomenon known as stereotype threat.
Research finds the threat comes in two flavours. Women can fear their poor performance will be used to bolster the “women are weak at maths” gender stereotype (known as “group-reputation threat”). Or they can fear that their poor performance will be taken as proof that they conform to the stereotype (“self-reputation threat”). Both can undermine women’s ability to fulfil their true potential.
A new study shows a simple way to alleviate the self-reputational aspect of stereotype threat. 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.
Overall, men outperformed women on the maths task. But women who took the test under someone else’s name, be it male or female, performed better than women who performed under their own name, and they did just as well as the men. The effect was stronger for women who cared more about maths.
By separating their performance from their own identity, it seems the women performing under an alias no longer felt pressure to avoid being seen as an example of the harmful gender stereotype. Further analysis showed this had to do with feeling less distracted during the task and with experiencing less self-repuational threat. In contrast, male performance was unaffected by using another person’s name.
Zhang and her team believe their findings have real-life applications for helping reduce the harm that comes from stereotype threat. “At the most practical level, they speak to the benefits of using non-name identification procedures in testing,” the researchers said. “But more generally, they suggest that coping strategies that allow stigmatised individuals to disconnect their self from a threatening situation can be an effective tool to disarm negative stereotypes.”
Shen Zhang, Toni Schmader, and William M. Hall (2013). L’eggo My Ego: Reducing the Gender Gap in Math by Unlinking the Self from Performance. Self and Identity DOI: 10.1080/15298868.2012.687012