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Garnett, E
Languages: English
Types: Doctoral thesis
In this thesis I examine scientific practices which produce data on air pollution, and the ways in which these data are managed and co-ordinated by researchers to make claims about air pollution. In doing so, I attend to the everyday practices and experiences of scientific research, exploring the ways in which science is a social and cultural endeavour. Based on three years ethnographic fieldwork with a multi-disciplinary project studying the relationship between Weather, Health and Air Pollution (WHAP), I trace the local meaning of research, but also its implications, as part of a wider ensemble of environmental health and policy relations.\ud Managing different data and co-ordinating research practices was understood by scientists as a fundamental part of doing ‘collaborative research’. Collaboration was performed through the movement of data, and also became an ethnographic device by which I traced and followed the activities of scientists. Working with data was considered ‘real’ scientific work, and it was this appeal to authenticity that led me to examine data as a form of material practice. The craftwork involved in the production and use of data illustrates the embodied and tacit nature of research. The way in which these different types of knowledge were negotiated by researchers shows that ‘objectivity’ is situated, and that scientific legitimacy is contingent on the social and technical configuration of tools, technologies, people and standards.\ud Drawing upon research from social and cultural studies of science, I emphasise both the representational and performative shape of science. The reciprocal nature of data practices configure and enact accepted ways of seeing air pollution which make scientific claims appear as ‘natural’ and logical. These not only represent air pollution but mobilise policy norms and modes of intervening, and therefore particular ideas, values and power dynamics. The chapters in this thesis explore the collection, production, processing and re-use of multiple air pollution data, and how the relations - of technologies, people and ideas - imbricated in data mobilise air pollution as an environmental health concern.
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