We conducted two studies to examine gender differences in in response to Facebook status updates. The first study surveyed 600 undergraduate students (388 females and 207 males), and analysed males' and females' responses to Facebook status updates. Females were significantly more likely to post a public reply than males, and female public replies also contained higher levels of emotional support. There were no significant gender differences in private replies to Facebook status updates. Males showed significantly higher levels of emotional support in private messages than in public replies.
Unfortunately, this approach does not scale well to large samples necessary for many analyses. We have since initiated systematic efforts to examine gender distributions of key populations of authors and reviewers for the Science family of journals using additional data and tools and plan to use this information to guide policy development and other appropriate steps to address any gender disparities. Since our initial study, we have collected gender and other demographic information voluntarily from approximately 5000 individuals (authors and reviewers). The automated tool provides inferred genders for more than 70% of the authors of both published and rejected Science papers submitted from 2010 to 2017. Based on comparisons with the individual-provided dataset, these inferred genders are more than 93% accurate on an individual basis.
There is a serious gender diversity crisis in AI research Only 13.83 per cent of authors are women and, in relative terms, the proportion of AI papers co-authored by at least one woman has not improved since the 1990s. Location and research domain are significant drivers of gender diversity Women in the Netherlands, Norway and Denmark are more likely to publish AI papers while those in Japan and Singapore are less likely to. The UK is 22nd on this list, with 26.62 per cent of AI papers having at least one female co-author. Women working in physics, education, computer ethics and other societal issues, and biology, are more likely to publish work on AI in comparison to those working in computer science or mathematics. There is a significant gender diversity gap in universities, big tech companies and other research institutions Apart from the University of Washington, every other academic institution and organisation in our dataset has less than 25 per cent female AI researchers.
Young girls and boys perform equally well in tests of intrinsic mathematical ability. Men are overrepresented in STEM (science, technology, engineering, and mathematics) fields. One proposed reason is that men hold an intrinsic advantage over women in mathematical cognition. If such an intrinsic difference exists, it should be present early in child development. To address this question, Kersey et al. examined data from more than 500 children ranging in age from 6 months to 8 years across several tests of numerosity, counting, and elementary mathematics concepts.
Editor's note: Francine D. Blau and Lawrence M. Kahn are economics professors at Cornell University. The research in this post is based on "The Gender Wage Gap: Extent, Trends and Explanations," an article Blau and Kahn co-wrote in the September, 2017 of the Journal of Economic Literature. This analysis is being published here in collaboration with EconoFact, a nonpartisan economic publication. In 2016 women who worked year-round and full-time earned, on average, around 81 cents for every dollar earned by men. Though still substantial, the difference in women's average earnings relative to men's has narrowed considerably since the 1970s.