Breaking the glass ceiling in science by looking at citations: Using artificial intelligence to study gender disparities in science

It’s 2022 and women in science are still less likely than their male peers to be hired and promoted. Women are less likely to be mentored by eminent faculty, they publish in less prestigious journals, have fewer collaborators, are underrepresented among journal reviewers and editors, and their papers receive fewer citations.

How. Is this. Happening?!

USC’s Information Sciences Institute (ISI) Principal Scientist Kristina Lerman and her team used AI to look for answers to this question. The resulting paper has been published in the prestigious, peer-reviewed, multi-disciplinary science journal Proceedings of the National Academy of Sciences (PNAS) on September 26, 2022.

As a woman in science herself, Lerman knows the world she works in, but even she was shocked by statistics she recently learned: only two percent of Nobel Prize winners in physics have been women (until a few years ago that was one percent) and those numbers are similar across many scientific fields. Lerman said, “only seven percent of Nobel Prize winners in chemistry have been women! Women have been working in chemistry for such a long time, so how is that? We were curious about this discrepancy.”

Right Data, Right Time

Lerman had the right dataset for the problem. Since 2019, she and her team had been working on a large project that used AI to predict the reproducibility of research papers. Funded by DARPA (the Defense Advanced Research Projects Agency), the ISI team used AI to analyze many aspects of scientific papers, including the citations, to predict reproducibility. They published the paper “Assessing Scientific Research Papers with Knowledge Graphs” at ACM SIGIR 22 (the Association for Computing Machinery’s Special Interest Group on Information Retrieval) in July 2022, describing their novel method and promising findings.

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