Machine-Learning Algorithm Quantifies Gender Bias in Astronomy

Researchers from the Swiss Federal Institute of Technology in Zurich, Switzerland, estimate that, as a result of gender bias, papers whose first authors are women receive around 10% fewer citations than do those that are first-authored by men. Gender disparities in citation patterns have been documented across science before. But researchers have not previously tried to quantify how much of the differences are the result of gender bias. For instance, men and women may publish different types of papers; women may work in different scientific fields, and may hold less-senior positions. But the new paper, which has not yet been peer-reviewed and was posted on the arXiv preprint server on October 27, tries to account and correct for these factors.