Maybe this is why the science industry is so male-dominated: Turns out science professors think more highly of male students. A team led by Corinne A. Moss-Racusin asked 127 professors of biology, chemistry, and physics at major research universities to rate the competency, hireability, and their own willingness to mentor of a grad school applicant on a scale of 1 to 7. Every professor got the same application except for one small difference: sometimes the aspiring scientist was named "John" and sometimes "Jennifer."  

Faculty—both men and women—rated the male student higher for everything. The chart above shows the average rating given to "John" or "Jennifer," whom the professors believed to be a real student who would read their evaluations. But the data in the paper, published by the Proceedings of the National Academy of Sciences, shows that female faculty actually rated "John" higher than their male colleagues, while they also gave lower ratings to "Jennifer." The biggest gap, both overall and depending on the gender of the rater, was in the hireability. "John" got hireability ratings of 3.74 and 3.92 from the male and female faculty. For "Jennifer," it was 2.96 and 2.84.

But especially worrying to the researchers were the competence ratings. The mean rating given to "John" by male professors was 4.01, while the mean rating by female professors was 4.1. For "Jennifer," the ratings were lower, but nearly identical by male and female faculty respondents: 3.33 and 3.32. Because students rely on positive professor feedback when deciding a career in science, the researchers write, "This finding raises the possibility that women may opt out of academic science careers in part because of diminished competence judgments, rewards, and mentoring received in the early years of the careers." 

Which is all to say, bias really does have an impact on the number of women in science. "Although women have begun to enter some science fields in greater numbers," the study says, "their mere increased presence is not evidence of the absence of bias."

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Serena Dai