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Subtle biases introduced in equity studies through data anonymization

2025-10-08Periodical Open access
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datacite.subject.fosEngenharia e Tecnologia
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorFazendeiro, Paulo
dc.contributor.authorPrata, Paula
dc.contributor.authorFerrão, Maria Eugénia
dc.contributor.editorAltman, Micah
dc.date.accessioned2025-12-03T09:45:35Z
dc.date.available2025-12-03T09:45:35Z
dc.date.issued2025-10-08
dc.description.abstractThis work investigates the trade-off between data anonymization and utility, particularly focusing on the implications for equity-related research in education. Using microdata from the 2019 Brazilian National Student Performance Exam (ENADE), the study applies the (ε, δ)-Differential Privacy model to explore the impact of anonymization on the dataset's utility for socio-educational equity analysis. By clustering both the original and anonymized datasets, the research evaluates how group categories related to students' sociodemographic variables, such as gender, race, income, and parental education, are affected by the anonymization process. The results reveal that while anonymization techniques can preserve overall data structure, they can also lead to the suppression or misrepresentation of minority groups, introducing biases that undermine the research's objective of promoting educational equity. This finding highlights the importance of involving domain experts in the interpretation of anonymized data, particularly in studies aimed at reducing socio-economic inequalities. The study concludes that careful attention is needed to prevent anonymization efforts from distorting key group categories, which could undermine the validity of data-driven policies aimed at promoting equity.eng
dc.identifier.citationFazendeiro P, Prata P, Ferrão ME (2025) Subtle biases introduced in equity studies through data anonymization. PLoS One 20(10): e0332441. https://doi.org/10.1371/journal.pone.0332441
dc.identifier.doi10.1371/journal.pone.0332441
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/10400.6/19409
dc.language.isoeng
dc.peerreviewedyes
dc.publisherPLOS
dc.relationInstituto de Telecomunicações
dc.relation.hasversionhttps://doi.org/10.1371/journal.pone.0332441
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleSubtle biases introduced in equity studies through data anonymizationeng
dc.typeperiodical
dcterms.referenceshttps://doi.org/10.17605/OSF.IO/P9M7N
dspace.entity.typePublication
oaire.awardTitleInstituto de Telecomunicações
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F50008%2F2013/PT
oaire.citation.issue10
oaire.citation.titlePLOS one
oaire.citation.volume20
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFazendeiro
person.familyNamePrata
person.familyNameFerrão
person.givenNamePaulo
person.givenNamePaula
person.givenNameMaria Eugénia
person.identifier.ciencia-id911F-3584-721F
person.identifier.ciencia-id651F-C1C8-44AD
person.identifier.orcid0000-0001-6054-7188
person.identifier.orcid0000-0002-3072-0186
person.identifier.orcid0000-0002-1317-0629
person.identifier.ridB-7713-2008
person.identifier.ridA-2665-2011
person.identifier.scopus-author-id19640174600
person.identifier.scopus-author-id6506143567
person.identifier.scopus-author-id24075949800
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublication47442970-f246-4908-b873-0b58e684a9e9
relation.isAuthorOfPublication138a0dac-5e5d-466c-901d-4ed34f860403
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relation.isAuthorOfPublication.latestForDiscovery138a0dac-5e5d-466c-901d-4ed34f860403
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