Gender imbalance in Wikipedia content is a known challenge which the editor community is actively addressing. The aim of this paper is to provide the Wikipedia community with instruments to estimate the magnitude of the problem for different entity types (also known as classes) in Wikipedia. To this end, we apply class completeness estimation methods based on the gender attribute. Our results show not only which gender for different sub-classes of Person is more prevalent in Wikipedia, but also an idea of how complete the coverage is for difference genders and sub-classes of Person.

翻译：维基百科内容的性别失衡现象是编辑社群正在积极应对的一项已知挑战。本文旨在为维基百科社群提供评估不同实体类型（也称类别）中该问题严重程度的工具。为此，我们基于性别属性应用了类别完整度估算方法。研究结果不仅揭示了"人物"类别下不同子类中哪个性别在维基百科中更具优势，还展示了不同性别及人物子类的覆盖完整程度。