A new Harvard study affirms that women are given less credit than men in co-authored articles; helps explain gender bias in hiring and tenure.
Author of study: Heather Sarsons
“This paper explores whether bias arising from group work helps explain the gender promotion gap. Using data from economists’ CVs, I test whether coauthored publications matter differently for tenure by gender. While solo-authored papers send a clear signal about one’s ability, coauthored papers do not provide specific information about each contributor’s skills. I find that women incur a penalty when they coauthor that men do not experience. This is most pronounced for women coauthoring with men and less pronounced the more women there are on a paper. A model shows that the bias documented here departs from traditional discrimination models.”
Excerpt: While the results presented in this paper are correlations, they provide suggestive evidence that gender bias exists in academic promotion decisions. The bias enters when workers send unclear signals (coauthored papers) that require some judgment on the part of the employer as to which worker made the greatest contribution. The data are not in line with a traditional model of statistical discrimination in which workers know their ability and anticipate employer discrimination. Women do not seem to coauthor strategically and employers do not treat coauthored papers as noisy signals for men. The results are more in line with a model in which workers do not know their ability or do not anticipate employer discrimination, and where employers update on signals differently for men and women.
Regardless, many occupations require group work. The tech industry, for example, prides itself on collaboration. In such male-dominated fields, however, group work in which a single output is produced could sustain the leaky pipeline if employers rely on stereotypes to attribute credit. I also studied a profession in which individuals can choose to collaborate. If workers are put in teams and do not have the choice to work on their own, the model’s predictions are amplified. Employers will rely primarily on their priors and women will be promoted at even lower rates. Bias, whether conscious or subconscious, can therefore have significant implications for the gender gap in promotion decisions.
The full article is online here.