Information Sciences Institute, University of Southern California, Marina del Rey, CA 90292.
School of Information, University of Michigan, Ann Arbor, MI 48109.
Proc Natl Acad Sci U S A. 2022 Oct 4;119(40):e2206070119. doi: 10.1073/pnas.2206070119. Epub 2022 Sep 26.
Diversity in science is necessary to improve innovation and increase the capacity of the scientific workforce. Despite decades-long efforts to increase gender diversity, however, women remain a small minority in many fields, especially in senior positions. The dearth of elite women scientists, in turn, leaves fewer women to serve as mentors and role models for young women scientists. To shed light on gender disparities in science, we study prominent scholars who were elected to the National Academy of Sciences. We construct author citation networks that capture the structure of recognition among scholars' peers. We identify gender disparities in the patterns of peer citations and show that these differences are strong enough to accurately predict the scholar's gender. In contrast, we do not observe disparities due to prestige, with few significant differences in the structure of citations of scholars affiliated with high-ranked and low-ranked institutions. These results provide further evidence that a scholar's gender plays a role in the mechanisms of success in science.
科学领域的多样性对于提高创新能力和增强科研人员队伍的能力至关重要。然而,尽管几十年来一直致力于提高性别多样性,但在许多领域,女性仍然只占少数,尤其是在高级职位上。杰出女科学家的匮乏,反过来又使得女性担任年轻女科学家的导师和榜样的人数减少。为了揭示科学界的性别差距,我们研究了入选美国国家科学院的杰出学者。我们构建了作者引用网络,以捕捉学者同行之间认可的结构。我们发现,在同行引用的模式中存在性别差距,并且这些差异足够大,可以准确预测学者的性别。相比之下,我们没有观察到因声望而产生的差异,高排名和低排名机构的学者的引用结构几乎没有显著差异。这些结果进一步证明,学者的性别在科学成功的机制中发挥了作用。