This paper attempts a first analysis of citation distributions based on the genderedness of authors' first name. Following the extraction of first name and sex data from all human entity triplets contained in Wikidata, a first name genderedness table is first created based on compiled sex frequencies, then merged with bibliometric data from eponymous, US-affiliated authors. Comparisons of various cumulative distributions show that citation concentrations fluctuations are highest at the opposite ends of the genderedness spectrum, as authors with very feminine and masculine first names respectively get a lower and higher share of citations for every article published, irrespective of their contribution role.

翻译：本文首次尝试基于作者名字的性别化程度分析引文分布。通过从Wikidata中所有人实体三元组中提取名字与性别数据，首先基于编译的性别频率创建名字性别化程度表，随后将其与美国籍同名作者的文献计量数据合并。对不同累积分布的比较表明，引文集中度的波动在性别化谱系的两端最为显著：无论其贡献角色如何，拥有非常女性化名字的作者每发表一篇文章获得的引文份额较低，而拥有非常男性化名字的作者则获得较高的引文份额。