Accounting for Complexity: Gene–environment Interaction Research and the Moral Economy of Quantification. (March 2016)

• Record Type: Journal Article
• Authors: Ackerman, Sara L.; Darling, Katherine Weatherford; Lee, Sandra Soo-Jin; Hiatt, Robert A.; Shim, Janet K.
• Is Part Of: Science, technology, & human values. Volume 41:Number 2(2016:Mar.)
• Page Start: 194
• Page End: 218
• Publication Date: 2016-03
• Subjects: moral economies -- quantification -- standarization -- genetics -- epidemiology; Science -- Social aspects -- Periodicals; Technology -- Social aspects -- Periodicals; Humanities -- Periodicals; 303.48305
• DOI: 10.1177/0162243915595462
• Languages: English
• ISSNs: 0162-2439

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.