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Published online by Cambridge University Press: 01 April 2022
Although epistemic values have become widely accepted as part of scientific reasoning, non-epistemic values have been largely relegated to the “external” parts of science (the selection of hypotheses, restrictions on methodologies, and the use of scientific technologies). I argue that because of inductive risk, or the risk of error, non-epistemic values are required in science wherever non-epistemic consequences of error should be considered. I use examples from dioxin studies to illustrate how non-epistemic consequences of error can and should be considered in the internal stages of science: choice of methodology, characterization of data, and interpretation of results.
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I gave earlier versions of this paper at the Workshop on Values in Scientific Research at the University of Pittsburgh in October 1998 and at the Center for Nuclear and Toxic Waste Management at the University of California at Berkeley in November 1999. My thanks to those whose challenges and comments at those talks helped me refine these ideas. I also wish to thank Ted Richards for his continual help on this paper.