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dc.contributor.authorLee, F
dc.contributor.authorBjörklund Larsen, L
dc.date.accessioned2021-10-12T12:25:17Z
dc.date.issued2019-08-13
dc.description.abstractThe power of algorithms has become a familiar topic in society, media, and the social sciences. It is increasingly common to argue that, for instance, algorithms automate inequality, that they are biased black boxes that reproduce racism, or that they control our money and information. Implicit in many of these discussions is that algorithms are permeated with normativities, and that these normativities shape society. The aim of this editorial is double: First, it contributes to a more nuanced discussion about algorithms by discussing how we, as social scientists, think about algorithms in relation to five theoretical ideal types. For instance, what does it mean to go under the hood of the algorithm and what does it mean to stay above it? Second, it introduces the contributions to this special theme by situating them in relation to these five ideal types. By doing this, the editorial aims to contribute to an increased analytical awareness of how algorithms are theorized in society and culture. The articles in the special theme deal with algorithms in different settings, ranging from farming, schools, and self-tracking to AIDS, nuclear power plants, and surveillance. The contributions thus explore, both theoretically and empirically, different settings where algorithms are intertwined with normativities.en_GB
dc.description.sponsorshipRiksbankens jubileumsfonden_GB
dc.identifier.citationVol. 6 (2)en_GB
dc.identifier.doi10.1177/2053951719867349
dc.identifier.urihttp://hdl.handle.net/10871/127422
dc.language.isoenen_GB
dc.publisherSAGE Publicationsen_GB
dc.rights© The Author(s) 2019. Open access. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).en_GB
dc.subjectalgorithmsen_GB
dc.subjecttheoryen_GB
dc.subjectnormativitiesen_GB
dc.subjectblack boxingen_GB
dc.subjectinfrastructuresen_GB
dc.subjectactor-network theoryen_GB
dc.titleHow should we theorize algorithms? Five ideal types in analyzing algorithmic normativitiesen_GB
dc.typeArticleen_GB
dc.date.available2021-10-12T12:25:17Z
dc.descriptionThis is the final version. Available on open access from SAGE Publications via the DOI in this recorden_GB
dc.identifier.eissn2053-9517
dc.identifier.journalBig Data and Societyen_GB
dc.rights.urihttps://www.creativecommons.org/licenses/by/4.0en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-08-13
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2021-10-12T12:23:30Z
refterms.versionFCDVoR
refterms.dateFOA2021-10-12T12:25:25Z
refterms.panelCen_GB


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© The Author(s) 2019. Open access. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
Except where otherwise noted, this item's licence is described as © The Author(s) 2019. Open access. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).