Authors
Eric Winsberg
University of South Florida
Wendy Parker
Virginia Tech
Abstract
We call attention to an underappreciated way in which non-epistemic values influence evidence evaluation in science. Our argument draws upon some well-known features of scientific modeling. We show that, when scientific models stand in for background knowledge in Bayesian and other probabilistic methods for evidence evaluation, conclusions can be influenced by the non-epistemic values that shaped the setting of priorities in model development. Moreover, it is often infeasible to correct for this influence. We further suggest that, while this value influence is not particularly prone to the problem of wishful thinking, it could have problematic non-epistemic consequences in some cases.
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DOI 10.1007/s13194-017-0180-6
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References found in this work BETA

Inductive Risk and Values in Science.Heather Douglas - 2000 - Philosophy of Science 67 (4):559-579.
In Defence of the Value Free Ideal.Gregor Betz - 2013 - European Journal for Philosophy of Science 3 (2):207-220.
Distinguishing Between Legitimate and Illegitimate Values in Climate Modeling.Kristen Intemann - 2015 - European Journal for Philosophy of Science 5 (2):217-232.

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Citations of this work BETA

Data models, representation and adequacy-for-purpose.Alisa Bokulich & Wendy Parker - 2021 - European Journal for Philosophy of Science 11 (1):1-26.

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