Suchergebnisse

Formerly a critical diagnosis, in the U.S. HIV is now classified as a chronic disease that can be survived and managed. From the early days of the AIDS crisis in the 1980s through the HAART (Highly Active Antiretroviral Treatments) era, HIV has remained an expensive illness. Many of the costs have been born by the public health systems of U.S. cities and states as well as the federal HIV program named for pioneering AIDS icon, Ryan White. In the mid-1990s, expensive but effective pharmaceutical HIV treatments called HAART became widely available through public and private health insurance in the U.S. Over the same time, cost containment strategies restructured US healthcare, and today inequalities remain entrenched in HIV health systems across the US and beyond. In this dissertation, I ask how and for whom HIV becomes "potentially chronic" and definitely expensive in the midst of US healthcare reforms. The biomedical and bureaucratic re-classifications of HIV as a chronic illness provide a case for examining how the problem of healthcare costs becomes linked to the bodies and lives of people and particular populations: What are the embodied and institutional consequences of HIV becoming a "life-long" disease? I ask what it means for HIV to be defined, managed and experienced as a chronic illness in U.S. healthcare and policy and what is at stake in this re-classification. In the context of managing costs and chronic conditions simultaneously, who has access to experiencing HIV as a chronic condition? How, why, and through what processes is this chronicity achievable for some people? Based at a San Francisco HIV clinic, an early epicenter of the HIV/AIDS epidemic that later became a hub of biomedical research and global model for HIV care, I ethnographically traced how patients and staff are navigating biomedical bureaucracies and health insurance markets as they attempt to obtain and provide healthcare. With an historical and ethnographic account of recent U.S. health care reform and its on-the-ground implementation at San Francisco General Hospital's HIV Outpatient HIV Clinic (Ward 86), I examine the production of chronicity as a state of ongoing illness or managed life. My data include: ethnographic observations, interviews with people living with HIV, healthcare providers and program administrators, and analysis of policy documents and archival materials. Drawing from theoretical traditions across racial theory, science and technology studies and medical sociology, I use my ethnographic reflections as a lens on the politics of insurance, healthcare finance, and personal health information within the context of stratified citizenship and speculative biocapitalism in the U.S.

STS theories of biocapital conceptualize how biomedical knowledge and capital form together. Though these formations of biocapital often are located in large urban centers, few scholars have attended to how they are transforming urban spaces and places. In this paper we argue that the twinned technological development of cells and cities concentrates economic and symbolic capital and sets in motion contentious practices we name urban biopolitics. We draw on archival research and a nearly decade-long ethnography of the expansion of biomedical campuses in a major American city to show how the speculative logics of land development and biomedical innovation become bound together in a process we describe as speculative revitalization. We examine how the logics of speculative revitalization imagine a future in which cities and biomedicine produce wealth and health harmoniously together. However, in practice—as buildings of new biomedical urban campuses get built—the dreams of billionaire philanthrocapitalists to create global cities clash with the plans of biomedical researchers to create global health. We document the reproduction of stratified and racialized biomedical exclusions that result while also highlighting the unlikely opportunities for creating alliances committed to creating equitable biomedical research and healthcare in urban communities.

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.

In this article, we explore current thinking and practices around the logics of difference in gene–environment interaction research in the post-genomic era. We find that scientists conducting gene–environment interaction research continue to invoke well-worn notions of racial difference and diversity, but use them strategically to try to examine other kinds of etiologically significant differences among populations. Scientists do this by seeing populations not as inherently homogeneous or heterogeneous, but rather by actively working to produce homogeneity along some dimensions and heterogeneity along others in their study populations. Thus we argue that homogeneity and heterogeneity are situational properties – properties that scientists seek to achieve in their study populations, the available data, and other aspects of the research situation they are confronting, and then leverage to advance post-genomic science. Pointing to the situatedness of homogeneity and heterogeneity in gene–environment interaction research underscores the work that these properties do and the contingencies that shape decisions about research procedures. Through a focus on the situational production of homogeneity and heterogeneity more broadly, we find that gene–environment interaction research attempts to shift the logic of difference from solely racial terms as explanatory ends unto themselves, to racial and other dimensions of difference that may be important clues to the causes of complex diseases.