Accounting for Complexity
Accounting for Complexity
复制标题
考虑复杂性
DOI：
--
复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Janet K Shim
中科院分区：
文献类型：
--
作者：
Sara L. Ackerman;K. W. Darling;S. Lee;R. Hiatt;Janet K Shim
科学家们现在同意，常见疾病是通过遗传和环境因素的相互作用而产生的，但对于科学研究应该如何解释这些相互作用，人们的共识较少。本文探讨了基因-环境相互作用（GEI）研究中的量化政治。根据对GEI研究人员的采访和观察，我们将量化描述为一种正在展开的科学道德经济，在这种经济中，研究人员集体制定相互竞争的“美德”。主要优点包括分子精确性，其中行为和社会风险因素被移入体内，以及“协调”，其中科学家在多地点联盟中创建大型数据集和共同利益。我们描述了谈判和权衡科学家制定，以产生可信的知识和形式的（自我）纪律，塑造研究人员，他们的做法，和研究对象。我们描述了流行的量化技术是如何在环境的萎缩中产生和谐的数据和和谐的科学家，导致一些科学家认为，社会，经济和政治对疾病模式的影响在后基因组研究中被边缘化。我们考虑如何各种GEI研究人员导航量化的生产力和限制性的影响，科学的病因复杂性。
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.
对于流行病学来说多大才算足够大？
DOI：
10.1097/01.ede.0000249507.52550.90
发表时间：
2007
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Kaplan,GeorgeA
通讯作者：
Kaplan,GeorgeA
影响因子：
7.7
作者：
Ioannidis, John P.A.;Boffetta, Paolo;Khoury, Muin J.
通讯作者：
Khoury, Muin J.