Article ID: CBB477913919

Making evidential claims in epidemiology: Three strategies for the study of the exposome (2020)

unapi

How is scientific data used to represent phenomena and as evidence for claims about phenomena? In this paper, I propose that a specific type of claims – evidential claims – is involved in data practices to define and restrict the representational and evidential content of a dataset. I present an account of data practices in the epidemiology of the exposome based on the notion of evidential claims, which helps unpack the approaches, assumptions and warrants that connect different stages of research. I identify three different strategies to generate different types of evidential claims in this case. The macro strategy, which individuates the dataset that serves as the initial evidential space for research. The micro strategy, which is used to generate evidential claims about the microscopic and individual component of target phenomena. The association strategy, that uses evidence from the other strategies to identify a dataset as representation of the different levels and relations of exposure and disease. Differentiating between these strategies sheds light on the multi-faceted landscape of biomedical research on environment and health; and the roles of data and evidence in the process of inquiry.

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Authors & Contributors
Achinstein, Peter
Colleen Derkatch
Sarah Ehlers
Frank Cabrera
Aviles, Natalie B.
Esselborn, Stefan
Journals
Studies in History and Philosophy of Science
Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences
Mefisto: Rivista di medicina, filosofia, storia
Social Studies of Science
Philosophy of Science
Metascience: An International Review Journal for the History, Philosophy and Social Studies of Science
Publishers
University of Chicago Press
Oxford University Press
Johns Hopkins University Press
Texas A&M University
Cambridge University Press
Taylor & Francis
Concepts
Evidence
Methodology of science; scientific method
Philosophy of science
Data analysis
Epidemiology
Medicine
People
Stern, Domenico Rigoni
Newton, Isaac
Lyell, Charles
Hill, Austin Bradford
Cicero, Marcus Tullius
Time Periods
20th century
19th century
17th century
21st century
20th century, late
18th century
Places
Americas
Denmark
Rome (Italy)
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