Social Studies of Science最新文献

The production of large, shareable datasets is increasingly prioritized for a wide range of research purposes. In biomedicine, especially in the United States, calls to enhance representation of historically underrepresented populations in databases that integrate genomic, health history, demographic and lifestyle data have also increased in order to support the goals of precision medicine. Understanding the assumptions and values that shape the design of such datasets and the practices through which they are constructed are a pressing area of social inquiry. We examine how diversity is conceptualized in U.S. precision medicine research initiatives, specifically attending to how measures of diversity, including race, ethnicity, and medically underserved status, are constructed and harmonized to build commensurate datasets. In three case studies, we show how symbolic embrace of both diversity and harmonization efforts can compromise the utility of diversity data. Although big data and diverse population representation are heralded as the keys to unlocking the promises of precision medicine research, these cases reveal core tensions between what kinds of data are seen as central to 'the science' and which are marginalized.

This comment critically examines Collins, Evans, and Reyes-Galindo's (CE&RG) concept of 'virtual diversity', proposed as a norm to safeguard scientific expertise in policy-making. CE&RG argue that scientists should acquire 'interactional expertise' in relevant 'non-scientific domains', enabling informed policy advice while preserving scientific integrity. This comment describes CE&RG's dualist approach, which separates epistemic and political concerns, and discusses its implications. It shows that for virtual diversity to contribute to the quality of and trust in expertise, this approach needs to be radically re-worked to include legitimacy-building processes. Using examples such as South Africa's AIDS policy and the COVID-19 pandemic, the comment argues that defending expertise requires ensuring the robustness of both scientific and political representations, of, in other terms, addressing expertise as a constitutional problem. Without a broader critical constitutional analysis, CE&RG's proposal risks reinforcing the crisis of expertise it seeks to remedy.

This is a commentary on 'Virtual diversity: Resolving the tension between the wider culture and the institution of science', by Harry Collins, Robert Evans, Luis Reyes-Galindo.

The opaque relationship between biology and behavior is an intractable problem for psychiatry, and it increasingly challenges longstanding diagnostic categorizations. While various big data sciences have been repeatedly deployed as potential solutions, they have so far complicated more than they have managed to disentangle. Attending to categorical misalignment, this article proposes one reason why this is the case: Datasets have to instantiate clinical categories in order to make biological sense of them, and they do so in different ways. Here, I use mixed methods to examine the role of the reuse of big data in recent genomic research on autism spectrum disorder (ASD). I show how divergent regimes of psychiatric categorization are innately encoded within commonly used datasets from MSSNG and 23andMe, contributing to a rippling disjuncture in the accounts of autism that this body of research has produced. Beyond the specific complications this dynamic introduces for the category of autism, this paper argues for the necessity of critical attention to the role of dataset reuse and recombination across human genomics and beyond.

There is growing concern around the world about declining trust in the scientific enterprise. Some STS scholars argue that the solution is to move to a system of 'virtual diversity' where scientists are responsible for translating public concerns into their work. This commentary argues that this containment approach will have the opposite effect. The history of similar efforts suggests that scientists have trouble understanding the scope and urgency of public frustrations, and devalue the contributions of non-scientists, damaging the social fabric. A better approach for producing socially useful science and enhancing public trust is to create a truly inclusive scientific enterprise, which takes the knowledge and priorities of non-scientists seriously and engages them throughout the investigative process.

There are widespread calls for increased demographic diversity in science, often linked to the epistemic claim that including more perspectives will improve the quality of the knowledge produced. By distinguishing between demographic and epistemic diversity, we show that this is only true some of the time. There are cases where increasing demographic diversity will not bring about the necessary epistemic diversity and cases where failing to exclude some voices reduces the quality of the scientific debate. We seek to resolve these tensions with an analysis that turns on the way the experience-based expertise of non-scientists can be absorbed into mainstream science. Mostly it has to be done via what we call 'virtual diversity', in which scientists take responsibility for acquiring interactional expertise in the non-scientific expertise-based domains which they consider provide knowledge valuable to the science. We argue that virtual diversity represents the only feasible option in most scenarios, with cases where demographic diversity or full cultural mergers provide the solution being the exception rather than the rule. This analysis is an exercise in the sociology of knowledge, which is considered as being continuous with philosophy. The paper is prescriptive as well as descriptive, and the moral, cultural, political, and educational implications of the argument are drawn out. A main conclusion is that the acquisition of virtual diversity should be a new norm for science, allowing the voices of experienced non-scientist citizens to be heard but without eroding the institution of science, which continues to be a vital foundation of truth in democracy.

There is a rich body of literature on numbers as tools of governance. But the attention of the corpus in question is almost entirely on the rational properties of quantification. This article shows that government by numbers is also, and inseparably, a government by feelings. The Covid-19 pandemic was also a datademic in the sense that numbers populated and spread through the public sphere. We focus on three cases. Death tolls were associated with fear, immunization rates were linked to hope, and the threshold of 100,000 deaths was credited with symbolic significance. This article, based on the French case, examines how data like these, frequently perceived as objective evidence, can at the same time be a source of emotional engagement and, as such, be used to inform modes of public governance in times of crises.

Drawing on ethnographic fieldwork, this paper unfolds the past and present uses of pigs that structured the emergence of a pig model of gut-hormone based appetite control, leading to the current scientific breakthrough in treatment of obesity. While the hyping of next generation medications for obesity and type 2 diabetes centers on the efficacy and profits attached to these drugs, I unfold how science embedded in this development had the in-vivo and in-vitro travels of Bettie-an obese Göttingen Minipig pig-at its heart. Tracing how she became embedded in a circuit of vitality connecting industrial agriculture and science on human health, I show how both are governed by a shared valuation of pigs' fat. Bettie's fat, however, was not to be eaten. Instead, Bettie was consumed in knowledge production. For pigs to enter this new trajectory, Bettie emerged as a promissory site for extraction of molecular information made possible by new visualization technologies and representational strategies that allowed for the coupling of human-pig physiology at the cellular level. While her travels were spurred by the hope of discovery of small molecules, Bettie allows us to grasp an important shift in science, as the insights derived from her work emphasized the importance of physiology and the environment for human obesity. In doing so, she served as a visceral model. On a larger scale, Bettie's entering science on human health reflects a recursive structure of knowledge in which the present problems with obesity and type 2 diabetes derive from the solutions to previous problems associated with alleviating hunger.