2026-06-16T06:31:02Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

cef7e3b02d5a78d68efdb41f0f09f3205172a752ad05786f1cabdffd5a97a764 2026-06-02T13:50:14Z language:enopenaire_data

DDI study level documentation for study 10.7802/2650 Data on the margins – Data from LGBTIQ+ Populations in European Social Science Data Archives Data on the margins – Data from LGBTIQ+ Populations in European Social Science Data Archives Data on the margins – Data from LGBTIQ+ Populations in European Social Science Data Archives 10.7802/265010.7802/265010.7802/265010.7802/2650 Perry, Anja Perry, Anja Recker, Jonas Recker, Jonas GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften sexualityhomosexualitybisexualitydataqueer studiessexualityhomosexualitybisexualitydataqueer studies A first step towards identifying and closing data gaps is to take stock of data that already exists. For this dataset, we collected 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 partner archives. Besides basic information to identify the datasets and their locations, we recorded temporal and spatial coverage, LGBTIQ+ identities sampled, access category, and keywords. In a separate dataset we take a closer look at the datasets’ keywords. We recorded information about language and whether a given keyword is related to LGBITQ+ identities. To describe the topics covered in the studies, the keywords were mapped to the CESSDA Topic Classification. A sentiment analysis with SentiStrength classifies whether a keyword has negative or positive/neutral sentiment. Additional keywords ( <a href="https://thesauri.cessda.eu/elsst-4/en/" target="_blank">https://thesauri.cessda.eu/elsst-4/en/ </a>): gender identity, genderqueer, LGBTQI+, non-binary persons, queer persons, transgender persons, sexual orientation, homosexuality, bisexuality, intersex personsA first step towards identifying and closing data gaps is to take stock of data that already exists. For this dataset, we collected 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 partner archives. Besides basic information to identify the datasets and their locations, we recorded temporal and spatial coverage, LGBTIQ+ identities sampled, access category, and keywords. In a separate dataset we take a closer look at the datasets’ keywords. We recorded information about language and whether a given keyword is related to LGBITQ+ identities. To describe the topics covered in the studies, the keywords were mapped to the CESSDA Topic Classification. A sentiment analysis with SentiStrength classifies whether a keyword has negative or positive/neutral sentiment. Additional keywords ( <a href="https://thesauri.cessda.eu/elsst-4/en/" target="_blank">https://thesauri.cessda.eu/elsst-4/en/ </a>): gender identity, genderqueer, LGBTQI+, non-binary persons, queer persons, transgender persons, sexual orientation, homosexuality, bisexuality, intersex persons All data records in member and partner archives of CESSDA ERIC. cross-sectioncross-section Non-probability Sample - Purposive SampleNon-probability Sample - Purposive Sample Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.Freier Zugang (ohne Registrierung) - Die Forschungsdaten können von jedem direkt heruntergeladen werden. http://dbkapps.gesis.org/dbkoai/oai.asp oai:dbk.gesis.org:SDN/10.7802_2650 2024-10-19 ddi:codebook:2_5