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关于文献语料库性别分析的思考

Reflections on Gender Analyses of Bibliographic Corpora.

作者信息

Mihaljević Helena, Tullney Marco, Santamaría Lucía, Steinfeldt Christian

机构信息

Hochschule für Technik und Wirtschaft Berlin, University of Applied Sciences, Berlin, Germany.

Technische Informationsbibliothek (TIB), Hanover, Germany.

出版信息

Front Big Data. 2019 Aug 28;2:29. doi: 10.3389/fdata.2019.00029. eCollection 2019.

Abstract

The interplay between an academic's gender and their scholarly output is a riveting topic at the intersection of scientometrics, data science, gender studies, and sociology. Its effects can be studied to analyze the role of gender in research productivity, tenure and promotion standards, collaboration and networks, or scientific impact, among others. The typical methodology in this field of research is based on a number of assumptions that are customarily not discussed in detail in the relevant literature, but undoubtedly merit a critical examination. Presumably the most confronting aspect is the categorization of gender. An author's gender is typically inferred from their name, further reduced to a binary feature by an algorithmic procedure. This and subsequent data processing steps introduce biases whose effects are hard to estimate. In this report we describe said problems and discuss the reception and interplay of this line of research within the field. We also outline the effect of obstacles, such as non-availability of data and code for transparent communication. Building on our research on gender effects on scientific publications, we challenge the prevailing methodology in the field and offer a critical reflection on some of its flaws and pitfalls. Our observations are meant to open up the discussion around the need and feasibility of more elaborated approaches to tackle gender in conjunction with analyses of bibliographic sources.

摘要

学者的性别与其学术产出之间的相互作用,是科学计量学、数据科学、性别研究和社会学交叉领域中一个引人入胜的话题。可以对其影响进行研究,以分析性别在研究生产力、 tenure和晋升标准、合作与网络或科学影响力等方面的作用。该研究领域的典型方法基于一些假设,这些假设在相关文献中通常没有详细讨论,但无疑值得进行批判性审视。大概最具挑战性的方面是性别的分类。作者的性别通常从其姓名中推断出来,通过算法程序进一步简化为二元特征。这以及随后的数据处理步骤会引入偏差,其影响难以估计。在本报告中,我们描述了上述问题,并讨论了该研究方向在该领域内的接受情况和相互作用。我们还概述了数据和代码不可用等障碍对透明交流的影响。基于我们对性别对科学出版物影响的研究,我们对该领域流行的方法提出质疑,并对其一些缺陷和陷阱进行批判性反思。我们的观察旨在开启围绕结合文献来源分析采用更精细方法来处理性别的必要性和可行性的讨论。

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