The paradigm of scientific medicine is among the most influential epistemic shifts in the past century, wherein randomized controlled trials (RCTs) represent the impartial arbiter of medical claims. Nevertheless, not all RCTs agree, and systematic reviews are invoked to reconcile them. We theorize how tacitness-beliefs, implicit assumptions, expectations, heuristics, unrecorded routines-accumulates within 'socio-epistemic bubbles', continuous regions of social density that decrease diversity and increase unwarranted certainty about healthcare studied by RCTs. To assess our theory, we analyze 20,117 meta-analyses extracted from 1,962 Cochrane systematic reviews. We find that being closer within 'social space' inscribed by scientific collaboration increases agreement across RCTs. Our analysis suggests that this amplified certainty can drive premature convergence affecting medical practice and population health. By increasing researchers' ability to perform an experiment in the way required to achieve an expected result, socio-epistemic bubbles represent the dark matter of the experimental process often obscured. Our findings imply hidden limitations associated with unmeasured social influence across the policy sciences, through which conflicting claims perpetuate and highlight the necessity of accounting for them to improve collective certainty.

There is an ongoing debate about the capacity of technologies to solve social problems. In this article, we analyze the sociomaterial scripts of three techno-fixes: cultured meat, social egg freezing, and AI assistants. Using a mix of ethnography, interviews, and discourse analysis, our case studies arrive at three findings. First, techno-fixes do not lead to a world with blurred boundaries and hybrid entities. On the contrary, clear images of nature, society, and technology serve as valuable resources in innovation processes. Second, technical solutions are based on three incompatible scripts. This makes it possible to revolutionize and save the world without changing it. We use the term non-disruptive disruption for this paradoxical invention. Third, techno-fixes are not science fiction, even if we encounter cells stored in cryobanks, steaks grown in bioreactors, or super-intelligent entities living in clouds. The doctors, biochemists, and programmers backstage reproduce social habits by incorporating conservative images into their innovations. By focusing on sociomaterial scripts, this article provides an analytical matrix for better understanding and evaluating techno-fixes in various areas of capitalist societies.

The belief in science's inherent self-corrective nature has been challenged by growing concerns over research integrity violations, leading to heightened scrutiny of scientific processes. Examining 40 years of discussions in Science and Nature, this article explores how debates on issues around research integrity reflect important shifts in the very meaning of 'scientific self' when speaking about the self-corrective capacity of science as well as evolving 'geographies of responsibility' within the research system. These journals-key voices in science and policy discourse-offer a lens to explore these processes of gradual transformation. We identify key narrative threads and turning points in understanding who is accountable for ensuring research integrity-extending beyond individual researchers to include institutions, funding bodies, journals, and whistleblowers. The analysis highlights how the scientific community has progressively reassembled its self-image, adapting to complex systemic challenges while engaging diverse stakeholders. These narratives, we argue, do more than document instances of transgressions of good scientific practice: They map broader transformations in the research ecosystem, revealing changing values, roles, and expectations. By analysing these shifts, we offer new insights into the interconnections between integrity concerns and systemic change, and into the conditions necessary for fostering responsible research practices and sustaining (public) trust in science.

Concerns over the complexity and costs of drug development have led some to consider whether practices of open science should be extended to pharmaceuticals, a space known for entrenched intellectual property regimes. In this article, I trace the emergence of collective action to apply open science to the research and making of drugs, an area I call open pharma. Drawing on in-depth interviews with open pharma leaders and document analysis of journal articles, organizational policies, and websites, I show that open pharma resembles other scientific/intellectual movements in developing new research practices and transmitting new ideas for sharing data. At the same time, the sociotechnical space of pharmaceuticals is deeply entwined in capitalist political economic structures (legal, regulatory, and financial markets) that shape how actors frame and organize their work. I identify key narratives that actors use to frame the movement and mobilize others, often drawing on market logics. I illustrate the active building and institutionalizing of open pharma infrastructure through the establishment of organizations and open science policies. And I describe structural barriers to open pharma in universities with publishing and commercialization imperatives-which are frequently translated into patent imperatives. 'Open' is often defined and operationalized in particular ways, prioritizing public data sharing of early research (which may later be privatized) over such interventions as public clinical trials and commercialization, raising the question of where, when, and for whom open pharma is beneficial.

Today, wet-bulb temperature is of vital importance in assessing the health effects of global warming. How did this heat stress index emerge? In this article, I turn to the research of industrial hygienist J.S. Haldane, who studied working conditions in mines in the early 20th century. The first warming of the thermo-industrial era was local, not global. It affected work environments, providing a fertile field of observation for occupational medicine and experimental physiology. These investigations revealed a wet-bulb temperature threshold beyond which efficiency deteriorates, which I interpret as the manifestation of an internal, climato-physiological contradiction between microclimates of production and labor power. However, as the long struggle of the Lancashire weavers against 'steaming' illustrates, an emerging labor environmentalism targeted these hostile atmospheric conditions. There, wet-bulb temperature and class struggle are combined in what I propose to call thermopolitics, which is understood as both government and conflict over temperatures. It was not just about controversies over regulatory standards; it was also about a clash between two opposing normativities, one quantitative, reduced to the physio-economy of productive efficiency, the other qualitative, vital, inviting us to rethink the notion of a democratic atmospheric politics. This article also shows that the theoretical wet-bulb temperature threshold used in some recent scientific literature is overestimated compared to empirical results exhumed from the history of science. This implies that, without decisive action, the tipping point for human heat tolerance could be reached sooner and more widely than anticipated.

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.

Psychiatry has recently witnessed the launch of digital phenotyping as a new research agenda. According to digital phenotyping's hypothesis, data about a patient's daily behavior can be continuously collected through wearable monitoring devices and used to build software that would send warnings of mental relapse or would tailor treatment choices. The research is exploratory, and the claims upon which it is based are contentious. Drawing on interviews, we followed a research team that aspired to build a digital system that could send such warnings to patients with mental health disorders like depression and epilepsy. This enabled us to learn how a new instrument to measure mental function becomes constructed and what translations take place in this process. Here we pay particular attention to the role of patients as research collaborators. We observed the frictions and debates in the research team between different mental health knowledge regimes, seeing them before they were black-boxed and lost from sight. We aimed to understand how actors anticipate software and data analytics to function alongside physicians and patients, as well as how different accounts reconstitute the 'mental', 'therapy', or the 'social' itself. We discuss several 'dissociations' that occur along the research trajectory regarding: less motivated and underrepresented patients, the role of clinical knowledge derived from patient self-reporting, and the social, political, and economic aspects of a patient's life affecting mental health. In this sense, we want to open the black box of this new behavioral technoscience.

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.

What is a diagnostic test for? We might assume the answer to this question is straightforward. A good test would help identify what disease someone suffers from, assist health providers to determine the correct course of treatment and/or enable public health authorities to know and intervene in health at the level of the population. In this article, we show that what a specific diagnostic test is for, the value it holds for different actors, and what makes it good, or not, is often far from settled. We tell the story of the development and design of a rapid antibody test for onchocerciasis, or river blindness, tracking multiple iterations of the device through three configurational moments in the framing of onchocerciasis disease and reshaping of the global health innovation ecosystem. Efforts to build that ecosystem for diagnostics are often premised on the notion that public health needs for diagnostics are pre-given and stable; the challenge is seen to be how to incentivize investment and find a customer base for diagnostics in under-resourced settings. By contrast, we show that for any disease, diagnostic needs are both multiple and constantly in flux, and are unlikely to be met by a single, stand-alone product. In the case of the onchocerciasis Ov-16 rapid test, the failure to recognize and address the multiplicity and instability of diagnostic needs in the innovation process resulted in the development of a rapid point of care test that might be manufactured, procured and used, but is unloved by public health experts and commercial manufacturers alike. The equivocal value of the onchocerciasis rapid test, we suggest, reveals the inadequacy of the current global health innovation ecosystem for developing diagnostic 'goods'.