It's a hard pill to swallow, but it's the truth: Gender bias is costing women opportunities in math and science careers. Women are still conspicuously outnumbered by men in those fields, even though more women enroll in undergraduate programs.
It seems that discrimination based on gender stereotypes is at least partly to blame, as explained in a new paper published in the Proceedings from the National Academy of Sciences, or PNAS. In "How stereotypes impair women's careers in science," three business school professors design an experiment to isolate discrimination's potential effect on hiring decisions.
What they found is sobering: When a hiring decision is solely on appearances, men are twice as likely as women to be hired for a mathematical task. When a hiring decision also includes the candidates' self-reported ability, women still lose out (men tend to overstate, women tend to understate, and hiring managers don't adjust for this).
The researchers, Ernesto Reuben of Columbia, Paola Sapienza of Northwestern Kellogg, and Luigi Zingales of Chicago Booth, did find a bit of evidence that preserves hope for aspiring women mathematicians and scientists. When hiring managers are given an "implicit association test," or IAT, and are able to see hard evidence of their math and science bias against women, their prejudice can be reduced.
Some of you may be wondering whether you're part of the problem. Some of you may just be curious. Whatever the case, you can take an IAT to test your own biases—of gender, as well as race, weight, age, religion, and more—and contribute to further research by participating in Project Implicit, a non-profit organization and international collaboration between researchers.
Seriously, go take an IAT right now, and brace yourself. When you're done with that, read this Reddit AMA with Project Implicit, and if you want more about the study, see what Shaila Dewan has to say at the New York Times Economix blog.