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Data on the Margins - Data from LGBTIQ+ Populations in European Social Science Data Archives
[journal article]
Abstract 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 ... view more
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. - Datenfile Version 1.0.0, https://doi.org/10.7802/2650... view less
Keywords
data capture; gender-specific factors; marginality; discrimination; data access; archives
Classification
Information and Documentation, Libraries, Archives
Women's Studies, Feminist Studies, Gender Studies
Free Keywords
social sciences; LGBTIQ+; research data; data archives; data gaps
Document language
English
Publication Year
2024
Page/Pages
p. 1-21
Journal
Data Science Journal, 23 (2024)
ISSN
1683-1470
Status
Published Version; peer reviewed
Licence
Creative Commons - Attribution 4.0
FundingThe publication was supported by the Leibniz Association's Open Access Publishing Fund for articles in open access journals.