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Accounting for Complexity: Gene-environment Interaction Research and the Moral Economy of Quantification.
Ackerman, Sara L; Darling, Katherine Weatherford; Lee, Sandra Soo-Jin; Hiatt, Robert A; Shim, Janet K.
Afiliação
  • Ackerman SL; Department of Social and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA.
  • Darling KW; Department of Social and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA.
  • Lee SS; Stanford Center for Biomedical Ethics and Program in Science, Technology and Society, Stanford University, Stanford, CA, USA.
  • Hiatt RA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
  • Shim JK; Department of Social and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA.
Sci Technol Human Values ; 41(2): 194-218, 2016 Mar 01.
Article em En | MEDLINE | ID: mdl-34456398
ABSTRACT
Scientists now agree that common diseases arise through interactions of genetic and environmental factors, but there is less agreement about how scientific research should account for these interactions. This paper examines the politics of quantification in gene-environment interaction (GEI) research. Drawing on interviews and observations with GEI researchers who study common, complex diseases, we describe quantification as an unfolding moral economy of science, in which researchers collectively enact competing ''virtues.'' Dominant virtues include molecular precision, in which behavioral and social risk factors are moved into the body, and ''harmonization,'' in which scientists create large data sets and common interests in multisited consortia. We describe the negotiations and trade-offs scientists enact in order to produce credible knowledge and the forms of (self-)discipline that shape researchers, their practices, and objects of study. We describe how prevailing techniques of quantification are premised on the shrinking of the environment in the interest of producing harmonized data and harmonious scientists, leading some scientists to argue that social, economic, and political influences on disease patterns are sidelined in postgenomic research. We consider how a variety of GEI researchers navigate quantification's productive and limiting effects on the science of etiological complexity.
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Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Tipo de estudo: Health_economic_evaluation Idioma: En Revista: Sci Technol Human Values Assunto da revista: CIENCIA / CIENCIAS SOCIAIS / ETICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Tipo de estudo: Health_economic_evaluation Idioma: En Revista: Sci Technol Human Values Assunto da revista: CIENCIA / CIENCIAS SOCIAIS / ETICA Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos