Research on large shared medical datasets and data-driven research are gaining fast momentum and provide major opportunities for improving health systems as well as individual care. Such open data can shed light on the causes of disease and effects of treatment, including adverse reactions side-effects of treatments, while also facilitating analyses tailored to an individual’s characteristics, known as personalized or “stratified medicine.” Developments, such as crowdsourcing, participatory surveillance, and individuals pledging to become “data donors” and the “quantified self” movement (where citizens share data through mobile device-connected technologies), have great potential to contribute to our knowledge of disease, improving diagnostics, and delivery of healthcare and treatment. There is not only a great potential but also major concerns over privacy, confidentiality, and control of data about individuals once it is shared. Issues, such as user trust, data privacy, transparency over the control of data ownership, and the implications of data analytics for personal privacy with potentially intrusive inferences, are becoming increasingly scrutinized at national and international levels. This can be seen in the recent backlash over the proposed implementation of care.data, which enables individuals’ NHS data to be linked, retained, and shared for other uses, such as research and, more controversially, with businesses for commercial exploitation. By way of contrast, through increasing popularity of social media, GPS-enabled mobile apps and tracking/wearable devices, the IT industry and MedTech giants are pursuing new projects without clear public and policy discussion about ownership and responsibility for user-generated data. In the absence of transparent regulation, this paper addresses the opportunities of Big Data in healthcare together with issues of responsibility and accountability. It also aims to pave the way for public policy to support a balanced agenda that safeguards personal information while enabling the use of data to improve public health.
In recent years the accessibility of London buses has improved with the introduction of ramps and wheelchair priority areas. These advances are meant to remove physical barriers to entering the bus, but new conflicts have arisen particularly over the physical space aboard. We aimed to research the barriers faced by wheelchair users in public transport using a mixed methods approach to establish the breadth of issues faced by wheelchair users. To this end we quantified the push-force used alight a bus and a study to understand the coping mechanisms used by people to propel up a ramp. This quantitative approach found push forces which resulted in a load of 2 to 3 times body weight being transferred through people's shoulders, forces which can be directly linked to shoulder injury. This could disable the user further, preventing them from being able to push their wheelchair. Alongside the quantitative study, we conducted qualitative research comprising of a number of in-depth interviews with wheelchair users about the barriers they face in public transport. Our main claim, highlighted through this interdisciplinary collaboration, is that proposed 'solutions' to accessibility, such as ramps, often generate problems of their own. These barriers can affect the life of wheelchair users, impacting on their confidence and causing social isolation. These can be long-term in nature or immediate.
The collapse of a tailings dam at the Samarco Mine in the Brazilian state of Minas Gerais on November 5th 2015 suddenly released around 62 million cubic meters of semi-liquid mining waste. The subsequent "wave of mud" (Creado and Helmereich 2018) travelled 879 km until reaching the Atlantic ocean, leaving a landscape of massive destruction, pollution, and death in its wake. The magnitude of the disaster immediately turned the spill into the worst environmental disaster in Brazil's history, according to most commentators. Then, on January 25th 2019, the collapse of another tailings dam at the Brumadinho Mine, located in the same Brazilian state and owned by the same mining corporation, killed at least 248 people, mostly mine workers, becoming the deadliest industrial disaster in Brazil's history. In just three years, a single region and company experienced two of the most polluting and deadliest disasters, not only in Brazil's history, but in Latin America as a whole. At the center of both disasters was the sudden collapse of a humble piece of mining infrastructure: a tailings dam. Simply defined in technical mining literature as "purposebuilt sedimentation lagoons" (Lottermoser 2007, 157), tailings dams are the place where all the unwanted leftovers of the mining extraction process come to rest, forever, materializing the "ultimate sink" (Tarr 1996) principle behind most mining enterprises worldwide. In most aspects, tailings dams appear as the ultimate example of a "boring" infrastructure, or complex pieces of technology that are "designed to become invisible as [they are] stabilized" (Lampland and Star 2009, 207). But then something happened. The ever-precarious balance between water and minerals that holds tailings dams together shifted in favor of water, and the dam collapsed. We will likely never know the exact moment or place where the collapse of the dams began, but in both cases the result was the same: destruction, death, and pollution. Everywhere. Brazil's twin mining disasters dramatically show us how infrastructures never become completely stabilized, or even invisible, in the first place. As a large body of STS literature has explored, instead of being perfectly immutable devices, infrastructures are highly paradoxical thingslarge and global, yet local and intimate; malleable, yet
Research impact on various societal spheres has been increasingly demanded for funding purposes and as a form of demonstrating the relevance of scientific research for societal problems. In this context, interest in interdisciplinary research and knowledge coproduction has grown as a path to achieve this expected impact, but few studies have considered its conjoint association with societal impact. This article investigates how academic research undertaken in interdisciplinary groups impacts public policies. To this end, we used a multiple case study strategy (involving three broad interdisciplinary research groups) to understand how the differences regarding knowledge coproduction with policy actors were relevant to explain differences in research impacts: instrumental, conceptual, symbolic and capacity-building. All the groups studied presented some type of impact in public policies, with emphasis on conceptual impact. The importance of knowledge coproduction was highlighted in two broad interdisciplinary groups since they stood out with more instrumental impacts compared to the other one. We argue that the combination of broad interdisciplinarity of the group together with the coproduction of knowledge with policymakers as co-researchers produces research that has more impact on the public policy community, especially translated as instrumental impact.
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