IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v7y2020i1d10.1057_s41599-020-00544-5.html
   My bibliography  Save this article

Moving back to the future of big data-driven research: reflecting on the social in genomics

Author

Listed:
  • Melanie Goisauf

    (University of Vienna
    BBMRI-ERIC)

  • Kaya Akyüz

    (University of Vienna
    BBMRI-ERIC)

  • Gillian M. Martin

    (University of Malta)

Abstract

With 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.

Suggested Citation

  • Melanie Goisauf & Kaya Akyüz & Gillian M. Martin, 2020. "Moving back to the future of big data-driven research: reflecting on the social in genomics," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-9, December.
  • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-00544-5
    DOI: 10.1057/s41599-020-00544-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-020-00544-5
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-020-00544-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Amy Maxmen, 2019. "Controversial ‘gay gene’ app provokes fears of a genetic Wild West," Nature, Nature, vol. 574(7780), pages 609-610, October.
    2. Aysu Okbay & Jonathan P. Beauchamp & Mark Alan Fontana & James J. Lee & Tune H. Pers & Cornelius A. Rietveld & Patrick Turley & Guo-Bo Chen & Valur Emilsson & S. Fleur W. Meddens & Sven Oskarsson & Jo, 2016. "Genome-wide association study identifies 74 loci associated with educational attainment," Nature, Nature, vol. 533(7604), pages 539-542, May.
    3. Jason M Fletcher, 2012. "Why Have Tobacco Control Policies Stalled? Using Genetic Moderation to Examine Policy Impacts," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-6, December.
    4. David Cyranoski, 2019. "Russian ‘CRISPR-baby’ scientist has started editing genes in human eggs with goal of altering deaf gene," Nature, Nature, vol. 574(7779), pages 465-466, October.
    5. Sheila Jasanoff & J. Benjamin Hurlbut, 2018. "A global observatory for gene editing," Nature, Nature, vol. 555(7697), pages 435-437, March.
    6. Michael Morrison & Stevienna de Saille, 2019. "CRISPR in context: towards a socially responsible debate on embryo editing," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-9, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Elena Popkova & Aleksei V. Bogoviz & Bruno S. Sergi, 2021. "Towards digital society management and ‘capitalism 4.0’ in contemporary Russia," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-8, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. von Hinke, Stephanie & Sørensen, Emil N., 2023. "The long-term effects of early-life pollution exposure: Evidence from the London smog," Journal of Health Economics, Elsevier, vol. 92(C).
    2. Nicholas W Papageorge & Kevin Thom, 2020. "Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study," Journal of the European Economic Association, European Economic Association, vol. 18(3), pages 1351-1399.
    3. Bierut, Laura & Biroli, Pietro & Galama, Titus J. & Thom, Kevin, 2023. "Challenges in studying the interplay of genes and environment. A study of childhood financial distress moderating genetic predisposition for peak smoking," Journal of Economic Psychology, Elsevier, vol. 98(C).
    4. Mitchell, Brittany L. & Hansell, Narelle K. & McAloney, Kerrie & Martin, Nicholas G. & Wright, Margaret J. & Renteria, Miguel E. & Grasby, Katrina L., 2022. "Polygenic influences associated with adolescent cognitive skills," Intelligence, Elsevier, vol. 94(C).
    5. Lyn Kathlene & Debashish Munshi & Priya Kurian & Sandra L. Morrison, 2022. "Cultures in the laboratory: mapping similarities and differences between Māori and non-Māori in engaging with gene-editing technologies in Aotearoa, New Zealand," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    6. Wendy Geuverink & Carla El & Martina Cornel & Bert Jan Lietaert Peerbolte & Janneke Gitsels & Linda Martin, 2023. "Between desire and fear: a qualitative interview study exploring the perspectives of carriers of a genetic condition on human genome editing," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-9, December.
    7. Barth, Daniel & Papageorge, Nicholas W. & Thom, Kevin, 2017. "Genetic Ability, Wealth, and Financial Decision-Making," IZA Discussion Papers 10567, Institute of Labor Economics (IZA).
    8. Samuel Baker & Pietro Biroli & Hans van Kippersluis & Stephanie von Hinke, 2022. "Beyond Barker: Infant Mortality at Birth and Ischaemic Heart Disease in Older Age," Bristol Economics Discussion Papers 22/765, School of Economics, University of Bristol, UK.
    9. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
    10. Viinikainen, Jutta & Bryson, Alex & Böckerman, Petri & Kari, Jaana T. & Lehtimäki, Terho & Raitakari, Olli & Viikari, Jorma & Pehkonen, Jaakko, 2022. "Does better education mitigate risky health behavior? A mendelian randomization study," Economics & Human Biology, Elsevier, vol. 46(C).
    11. Morten Dybdahl Krebs & Gonçalo Espregueira Themudo & Michael Eriksen Benros & Ole Mors & Anders D. Børglum & David Hougaard & Preben Bo Mortensen & Merete Nordentoft & Michael J. Gandal & Chun Chieh F, 2021. "Associations between patterns in comorbid diagnostic trajectories of individuals with schizophrenia and etiological factors," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    12. Chris Bidner & John Knowles, 2018. "Matching for Social Mobility with Unobserved Heritable Characteristics," Discussion Papers dp18-05, Department of Economics, Simon Fraser University.
    13. Lauren L. Schmitz & Dalton Conley, 2016. "The Effect of Vietnam-Era Conscription and Genetic Potential for Educational Attainment on Schooling Outcomes," NBER Working Papers 22393, National Bureau of Economic Research, Inc.
    14. Brooke M Huibregtse & Breanne L Newell-Stamper & Benjamin W Domingue & Jason D Boardman & Anna Zajacova, 2021. "Genes Related to Education Predict Frailty Among Older Adults in the United States [Genetic analysis of social-class mobility in five longitudinal studies]," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 76(1), pages 173-183.
    15. Jason M. Fletcher & Qiongshi Lu, 2021. "Health policy and genetic endowments: Understanding sources of response to Minimum Legal Drinking Age laws," Health Economics, John Wiley & Sons, Ltd., vol. 30(1), pages 194-203, January.
    16. van den Berg, Gerard J. & Modin, Bitte, 2013. "Economic Conditions at Birth, Birth Weight, Ability, and the Causal Path to Cardiovascular Mortality," IZA Discussion Papers 7605, Institute of Labor Economics (IZA).
    17. Liang, X.; & Sanderson, E.; & Windmeijer, F.;, 2022. "Selecting Valid Instrumental Variables in Linear Models with Multiple Exposure Variables: Adaptive Lasso and the Median-of-Medians Estimator," Health, Econometrics and Data Group (HEDG) Working Papers 22/22, HEDG, c/o Department of Economics, University of York.
    18. Fletcher, Jason, 2023. "Decoupling genetics from attainments: The role of social environments," Economics & Human Biology, Elsevier, vol. 50(C).
    19. Gerard J. van den Berg & Stephanie von Hinke & Nicolai Vitt, 2023. "Early life exposure to measles and later-life outcomes: Evidence from the introduction of a vaccine," Bristol Economics Discussion Papers 23/776, School of Economics, University of Bristol, UK.
    20. Fletcher, Jason & Kumar, Sanjeev, 2014. "Religion and risky health behaviors among U.S. adolescents and adults," Journal of Economic Behavior & Organization, Elsevier, vol. 104(C), pages 123-140.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-00544-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.