The Gender Equation
A few years ago, economics professor Glenn Ellison, PhD ‘92, started coaching the math team at his daughters’ middle school near Boston. The all-girls squad consisted of his oldest daughter and her friends, and they made a run to the state finals. But Ellison noticed something striking. “We would go to math contests, and my team didn’t look like other teams,” he says. The others were made up almost entirely of boys.

Ellison’s casual observation turns out to reflect the underlying fact that high-achieving female math students are much more common at some schools than others, suggesting that environmental factors, not just innate ability, are shaping student performance. Now Ellison and Ashley Swanson, a PhD student in economics, have quantified this effect in a paper that will appear in the Journal of Economic Perspectives this year.
They found that in the annual American Mathematics Competitions (AMC), which involve 125,000 high-school students, boys outnumber girls six to one at the 99th percentile and 12 to one at the 99.9th percentile. Some of these students compete in international math competitions–and more than half the girls on U.S. teams come from just 20 high schools, including New Hampshire’s Phillips Exeter Academy and several public schools in Northern California.
“It’s significant that the top girls are coming from a very, very small subset of schools with strong math programs,” says Ellison. “That suggests most of the girls who could be doing well aren’t doing well.” Moreover, Ellison and Swanson write, the gender gap in math may be related to the underrepresentation of women in scientific fields. Bright girls who shun math may never pursue science careers, limiting the pool of researchers.
Ellison and Swanson would like to create a longitudinal study of female students and investigate why they either continue with or disengage from math. And they are using the AMC data to see if math achievement correlates with specific academic practices. “There is a variation across these schools that can’t be explained by income or demographics,” says Ellison. “We’re looking for environments where girls are doing better and worse, and using that variation to try to understand what’s causing it and what can improve the situation.”
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