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Frontmatter -- Contents -- Acknowledgments -- Introduction -- 1. The Politics of Disease Causation -- 2. Disciplining Difference -- 3. The Contested Meanings and Intersections of Race -- 4. An Apparent Consensus on Class -- 5. The Dichotomy of Gender -- 6. Individualizing "Difference" and the Production of Scientific Credibility -- Conclusion -- Appendix: Methodology -- Notes -- References -- Index -- About the Author

- In this article, we review the history of medicalization theory and then offer a historicized definition of biomedicalization. We consider the relationships between biomedicalization and other contemporary theorizing, seeking in particular to situate the concept explicitly in relation to recent scholarship on the politics of life itself. We discuss how biomedicalization processes dovetail with such politics of life as they are engaged individually, collectively, and at the level of population, including issues of bioeconomy, biocapital, citizenship and enhancement. We then address and respond to several critiques of biomedicalization theory, that question its newness, omnipresence, and determinism. In conclusion, we discuss the relations among medicalization, biomedicalization and medical sociology and offer directions for future research.Keywords: biomedicalization, medicalization, technoscience, health, politics of life, optimization.Parole chiave: biomedicalizzazione, medicalizzazione, tecnoscienza, salute, politica della vita, ottimizzazione.

This paper articulates how political ecology can be a useful tool for asking fundamental questions and applying relevant methods to investigate structures that impact relationship between neighborhood and health. Through a narrative analysis, we identify how political ecology can develop our future agendas for neighborhood-health research as it relates to social, political, environmental, and economic structures. Political ecology makes clear the connection between political economy and neighborhood by highlighting the historical and structural processes that produce and maintain social inequality, which affect health and well-being. These concepts encourage researchers to examine how people construct neighborhood and health in different ways that, in turn, can influence different health outcomes and, thus, efforts to address solutions.

The quality of the collaboration between health professionals and caregivers is of great significance to outcome and recovery. Severe brain injuries after a stroke can leave patients unable to communicate their needs and wishes with health professionals, in which case the role of the caregiver(s) becomes even more important. This position is highly differentiated, and there are substantial variations in how caregivers participate in the collaboration. Using the Bourdieusian concept of cultural health capital, we aimed to develop a broader understanding of the role played by the patient's caregiver and how inequality is produced in the encounter with professionals. This qualitative study was conducted from 2014 to 2018. We observed the meetings and interactions between caregivers and health professionals during patients' neurorehabilitation after a stroke, and we interviewed caregivers and health professionals on their experiences during this period. Constructing three different caregiver types—the proactive, the persistent, and the deferential—we discovered different ways of interacting and different attitudes related to cultural health capital, which provided the caregiver with more or fewer opportunities to participate in a dialogue and negotiation on behalf of the patient.

Biomedical research is increasingly informed by expectations of "translation," which call for the production of scientific knowledge that can be used to create services and products that improve health outcomes. In this paper, we ask how translation, in particular the idea of social responsibility, is understood and enacted in the post-genomic life sciences. Drawing on theories examining what constitutes "good science," and interviews with 35 investigators who study the role of gene-environment interactions in the etiology of cancer, diabetes, and cardiovascular disease, we describe the dynamic and unsettled ethics of translational science through which the expected social value of scientific knowledge about complex disease causation is negotiated. To describe how this ethics is formed, we first discuss the politics of knowledge production in interdisciplinary research collectives. Researchers described a commitment to working across disciplines to examine a wide range of possible causes of disease, but they also pointed to persistent disciplinary and ontological divisions that rest on the dominance of molecular conceptions of disease risk. The privileging of molecular-level causation shapes and constrains the kinds of knowledge that can be created about gene-environment interactions. We then turn to scientists' ideas about how this knowledge should be used, including personalized prevention strategies, targeted therapeutics, and public policy interventions. Consensus about the relative value of these anticipated translations was elusive, and many scientists agreed that gene-environment interaction research is part of a shift in biomedical research away from considering important social, economic, political and historical causes of disease and disease disparities. We conclude by urging more explicit engagement with questions about the ethics of translational science in the post-genomic life sciences. This would include a consideration of who will benefit from emerging scientific knowledge, how benefits will accrue, and the ways in which normative assumptions about the public good come to be embedded in scientific objects and procedures.

Biomedical research is increasingly informed by expectations of "translation," which call for the production of scientific knowledge that can be used to create services and products that improve health outcomes. In this paper, we ask how translation, in particular the idea of social responsibility, is understood and enacted in the post-genomic life sciences. Drawing on theories examining what constitutes "good science," and interviews with 35 investigators who study the role of gene-environment interactions in the etiology of cancer, diabetes, and cardiovascular disease, we describe the dynamic and unsettled ethics of translational science through which the expected social value of scientific knowledge about complex disease causation is negotiated. To describe how this ethics is formed, we first discuss the politics of knowledge production in interdisciplinary research collectives. Researchers described a commitment to working across disciplines to examine a wide range of possible causes of disease, but they also pointed to persistent disciplinary and ontological divisions that rest on the dominance of molecular conceptions of disease risk. The privileging of molecular-level causation shapes and constrains the kinds of knowledge that can be created about gene-environment interactions. We then turn to scientists' ideas about how this knowledge should be used, including personalized prevention strategies, targeted therapeutics, and public policy interventions. Consensus about the relative value of these anticipated translations was elusive, and many scientists agreed that gene-environment interaction research is part of a shift in biomedical research away from considering important social, economic, political and historical causes of disease and disease disparities. We conclude by urging more explicit engagement with questions about the ethics of translational science in the post-genomic life sciences. This would include a consideration of who will benefit from emerging scientific knowledge, how benefits will ...

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.

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.

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.

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.