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dc.contributor.authorGoisauf, Melanie-
dc.contributor.authorAkyüz, Kaya-
dc.contributor.authorMartin, Gillian M.-
dc.date.accessioned2020-09-07T09:12:52Z-
dc.date.available2020-09-07T09:12:52Z-
dc.date.issued2020-
dc.identifier.citationGoisauf, M., Akyüz, K., & Martin, G. M. (2020). Moving back to the future of big data-driven research: reflecting on the social in genomics. Humanities and Social Sciences Communications, 7(1), 1-9.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/60274-
dc.description.abstractWith the advance of genomics, specific individual conditions have received increased attention in the generation of scientific knowledge. This spans the extremes of the aim of curing genetic diseases and identifying the biological basis of social behaviour. In this development, the ways knowledge is produced have gained significant relevance, as the data-intensive search for biology/sociality associations has repercussions on doing social research and on theory. This article argues that an in-depth discussion and critical reflection on the social configurations that are inscribed in, and reproduced by genomic data-intensive research is urgently needed. This is illustrated by debating a recent case: a large-scale genome-wide association study (GWAS) on sexual orientation that suggested partial genetic basis for same-sex sexual behaviour (Ganna et al. 2019b). This case is analysed from three angles: (1) the demonstration of how, in the process of genomics research, societal relations, understandings and categorizations are used and inscribed into social phenomena and outcomes; (2) the exploration of the ways that the (big) data-driven research is constituted by increasingly moving away from theory and methodological generation of theoretical concepts that foster the understanding of societal contexts and relations (Kitchin 2014a). Big Data Soc and (3) the demonstration of how the assumption of ‘free from theory’ in this case does not mean free of choices made, which are themselves restricted by data that are available. In questioning how key sociological categories are incorporated in a wider scientific debate on genetic conditions and knowledge production, the article shows how underlying classification and categorizations, which are inherently social in their production, can have wide ranging implications. The conclusion cautions against the marginalization of social science in the wake of developments in data-driven research that neglect social theory, established methodology and the contextual relevance of the social environment.en_GB
dc.language.isoenen_GB
dc.publisherSpringer Natureen_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectManagement -- Study and teachingen_GB
dc.subjectOrganization -- Study and teachingen_GB
dc.subjectQuantitative researchen_GB
dc.subjectGenomics -- Researchen_GB
dc.titleMoving back to the future of big data-driven research : reflecting on the social in genomicsen_GB
dc.typearticleen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holderen_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.1057/s41599-020-00544-5-
dc.publication.titleHumanities and Social Sciences Communicationsen_GB
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