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Despite the widespread use of key concepts of the Neyman–Pearson (N–P) statistical paradigm—type I and II errors, significance levels, power, confidence levels—they have been the subject of philosophical controversy and debate for over 60 years. Both current and long-standing problems of N–P tests stem from unclarity and confusion, even among N–P adherents, as to how a test's (pre-data) error probabilities are to be used for (post-data) inductive inference as opposed to inductive behavior. We argue that the relevance of error probabilities (...) |
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Who is right? In Risk and Rationality, Kristin Shrader-Frechette argues that neither charges of irresponsible endangerment nor countercharges of scientific illiteracy frame the issues properly. |
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Comparing alternative scientific theories obviously is relevant to theory assessment, but are comparativists (like Laudan) correct when they also make it necessary? This paper argues that they are not. Defining rationality solely in terms of theories' comparative problem-solving strengths, comparativist philosophers of science like Laudan subscribe to what I call the irrelevance claim (IC) and the necessity claim (NC). According to IC, a scientific theory's being well or poorly confirmed is "irrelevant" to its acceptance; NC is the claim that "all (...) |
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In this book, Carl Cranor utilizes material from ethics, philosophy of law, epidemiology, tort law, regulatory law, and risk assessment to argue that the evidentiary standards for science used in the law to control toxics ought to be ... |
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The biological effects of low doses of toxic and carcinogenic chemicals are currently a matter of significant scientific controversy. This paper argues that philosophers of science can contribute to alleviating this controversy by examining it with the aid of a novel account of scientific anomaly. Specifically, analysis of contemporary research on chemical hormesis (i.e., alleged beneficial biological effects produced by low doses of substances that are harmful at higher doses) suggests that scientists may initially describe anomalous phenomena in terms of (...) |
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I argue that although the judgments required to reach statistical risk assessments may reflect policy values, it does not follow that the task of evaluating whether a given risk assessment is warranted by the evidence need also be imbued with policy values. What has led many to conclude otherwise, I claim, stems from misuses of the statistical testing methods involved. I set out rules for interpreting what specific test results do and do not say about the extent of a given (...) |
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