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The extent and drivers of gender imbalance in neuroscience reference lists
bioRxiv - Scientific Communication and Education Pub Date : 2020-04-09 , DOI: 10.1101/2020.01.03.894378
Jordan D. Dworkin , Kristin A. Linn , Erin G. Teich , Perry Zurn , Russell T. Shinohara , Danielle S. Bassett

Like many scientific disciplines, neuroscience has increasingly attempted to confront pervasive gender imbalances within the field. While much of the conversation has centered around publishing and conference participation, recent research in other fields has called attention to the prevalence of gender bias in citation practices. Because of the downstream effects that citations can have on visibility and career advancement, understanding and eliminating gender bias in citation practices is vital for addressing inequity in a scientific community. In this study, we sought to determine whether there is evidence of gender bias in the citation practices of neuroscientists. Using data from five top neuroscience journals, we find that reference lists tend to include more papers with men as first and last author than would be expected if gender were not a factor in referencing. Importantly, we show that this overcitation of men and undercitation of women is driven largely by the citation practices of men, and is increasing over time as the field becomes more diverse. We develop a co-authorship network to assess homophily in researchers’ social networks, and we find that men tend to overcite men even when their social networks are representative. We discuss possible mechanisms and consider how individual researchers might address these findings in their own practices.

中文翻译:

神经科学参考清单中性别不平衡的程度和驱动因素

像许多科学学科一样,神经科学越来越多地尝试解决该领域内普遍存在的性别失衡问题。尽管大部分对话都围绕出版和会议参与进行,但其他领域的最新研究要求人们关注引文实践中性别偏见的普遍性。由于引用可能会对可见度和职业发展产生下游影响,因此理解和消除引用行为中的性别偏见对于解决科学界的不平等现象至关重要。在这项研究中,我们试图确定在神经科学家的引用实践中是否存在性别偏见的证据。利用来自五种顶级神经科学期刊的数据,我们发现,参考文献列表中包含的论文多为男性,第一作者和最后作者比如果性别不是参考文献的因素所期望的要多。重要的是,我们表明,这种对男性的过度引用和对女性的不充分引用在很大程度上是由男性的引用实践所驱动的,并且随着时间的流逝,随着领域的日益多样化,这种引用在增加。我们建立了一个共同作者网络来评估研究人员的社交网络中的同质性,并且我们发现,即使在社交网络具有代表性的情况下,男性也往往会超过男性。我们讨论了可能的机制,并考虑了各个研究人员如何在自己的实践中解决这些发现。并且随着时间的推移,该领域变得越来越多样化。我们开发了一个共同作者网络来评估研究人员的社交网络中的同质性,并且我们发现,即使在社交网络具有代表性的情况下,男性也往往会超过男性。我们讨论了可能的机制,并考虑了各个研究人员如何在自己的实践中解决这些发现。并且随着时间的推移,该领域变得越来越多样化。我们建立了一个共同作者网络来评估研究人员的社交网络中的同质性,并且我们发现,即使在社交网络具有代表性的情况下,男性也往往会超过男性。我们讨论了可能的机制,并考虑了各个研究人员如何在自己的实践中解决这些发现。
更新日期:2020-04-09
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