边缘数据--欧洲社会科学数据档案中的 LGBTIQ+ 人口数据

Q2 Computer Science
Jonas Recker, Anja Perry
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引用次数: 0

摘要

数据缺口是指由于不平等的权力关系而导致的边缘化群体数据的严重缺乏(D'Ignazio and Klein, 2020)。在我们认识世界和与世界互动的过程中,男性、白人、异性恋和同性视角占主导地位,这既延续了这种现象,也造成了这种现象。克里亚多-佩雷斯(Criado-Perez,2020 年)指出,最突出的数据鸿沟是性别数据鸿沟。然而,不仅是妇女,所有边缘化群体都受到这种差距的影响,因为由于当权者无视收集数据的必要性,有关他们的数据经常得不到收集。被人口学家视为 "隐性人口 "的 LGBTIQ+ 就是一个很好的例子。这个缩写指的是女同性恋、男同性恋、双性恋、变性人、双性人和同性恋者,以及所有具有非规范性身份或性别认同的人,包括无性人和变性人,但他们并不认为自己属于这些标签中的一种。本文概述了欧洲社会科学档案中的 LGBTIQ+ 数据。我们研究了欧洲社会科学数据档案联盟(CESSDA ERIC)的所有数据档案,在 34 个成员和相关档案中的 9 个以及 1 个前成员档案中发现了 66 个 LGBTIQ+ 数据集。我们讨论了已识别数据集的特征、覆盖范围和可查找性,并通过分析档案馆分配给每个数据集的关键词来探讨潜在的数据缺口问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data on the Margins – Data from LGBTIQ+ Populations in European Social Science Data Archives
Data gaps are a significant lack of data about marginalized groups existing due to unequal power relations (D’Ignazio and Klein, 2020). They both perpetuate and result in a dominance of male, white, hetero, and cis perspectives in how we make sense of and interact with the world. The most prominent data gap is the gender data gap notably described by Criado-Perez (2020). However, not only women, but all marginalized groups are affected by such gaps, as data about them are frequently not collected due to a disregard on behalf of those in power of the need to do so. LGBTIQ+ people, considered a ‘hidden population’ by demographers, are a case in point. The acronym is used to refer to lesbian, gay, bisexual, trans, intersex, and queer people, as well as all people with non-normative sexual or gender identities, including asexual and agender people, who do not consider themselves as falling under one of these labels. A first step towards identifying and closing data gaps is to take stock of data that already exist. In this paper we give an overview of LGBTIQ+ data in European social science archives. We researched all data archives of CESSDA ERIC, the Consortium of European Social Science Data Archives, and found 66 LGBTIQ+ datasets in 9 of the 34 member and associated archives and 1 former member archive. We discuss characteristics, coverages, and findability of the identified datasets and approach the question of potential data gaps by analyzing the keywords assigned to each dataset by the archive.
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来源期刊
Data Science Journal
Data Science Journal Computer Science-Computer Science (miscellaneous)
CiteScore
5.40
自引率
0.00%
发文量
17
审稿时长
10 weeks
期刊介绍: The Data Science Journal is a peer-reviewed electronic journal publishing papers on the management of data and databases in Science and Technology. Details can be found in the prospectus. The scope of the journal includes descriptions of data systems, their publication on the internet, applications and legal issues. All of the Sciences are covered, including the Physical Sciences, Engineering, the Geosciences and the Biosciences, along with Agriculture and the Medical Science. The journal publishes papers about data and data systems; it does not publish data or data compilations. However it may publish papers about methods of data compilation or analysis.
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