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The Methods of Science: No Dogs or Philosophers AllowedDVD. forthcoming.What is science, and what is it not? Is falsifiability the key to drawing this line? How and why does science work? Should we worry whether science is talking about a "real" world? And should we stop thinking there is a single thing we can call "the scientific method"? With Deborah Mayo, Robert Rynasiewicz, and Drew Arrowood
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80Philosophical Scrutiny of Evidence of Risks: From Bioethics to BioevidencePhilosophy of Science 73 (5): 803-816. 2006.We argue that a responsible analysis of today's evidence-based risk assessments and risk debates in biology demands a critical or metascientific scrutiny of the uncertainties, assumptions, and threats of error along the manifold steps in risk analysis. Without an accompanying methodological critique, neither sensitivity to social and ethical values, nor conceptual clarification alone, suffices. In this view, restricting the invitation for philosophical involvement to those wearing a "bioethicist…Read more
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122Novel evidence and severe testsPhilosophy of Science 58 (4): 523-552. 1991.While many philosophers of science have accorded special evidential significance to tests whose results are "novel facts", there continues to be disagreement over both the definition of novelty and why it should matter. The view of novelty favored by Giere, Lakatos, Worrall and many others is that of use-novelty: An accordance between evidence e and hypothesis h provides a genuine test of h only if e is not used in h's construction. I argue that what lies behind the intuition that novelty matter…Read more
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38Frequentist statistics as a theory of inductive inferenceIn Deborah G. Mayo & Aris Spanos (eds.), Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science, Cambridge University Press. 2009.After some general remarks about the interrelation between philosophical and statistical thinking, the discussion centres largely on significance tests. These are defined as the calculation of p-values rather than as formal procedures for ‘acceptance‘ and ‘rejection‘. A number of types of null hypothesis are described and a principle for evidential interpretation set out governing the implications of p- values in the specific circumstances of each application, as contrasted with a long-run inter…Read more
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47Toward progressive critical rationalism : exchanges with Alan MusgraveIn Deborah G. Mayo & Aris Spanos (eds.), Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science, Cambridge University Press. pp. 113. 2009.
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60Error and Inference: Recent Exchanges on Experimental Reasoning, Reliability, and the Objectivity and Rationality of Science (edited book)Cambridge University Press. 2009.Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Phil…Read more
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75An objective theory of statistical testingSynthese 57 (3). 1983.Theories of statistical testing may be seen as attempts to provide systematic means for evaluating scientific conjectures on the basis of incomplete or inaccurate observational data. The Neyman-Pearson Theory of Testing (NPT) has purported to provide an objective means for testing statistical hypotheses corresponding to scientific claims. Despite their widespread use in science, methods of NPT have themselves been accused of failing to be objective; and the purported objectivity of scientific cl…Read more
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16Scientific Reasoning: The Bayesian Approach. Colin Howson, Peter UrbachIsis 82 (4): 788-789. 1991.
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95Peircean Induction and the Error-Correcting ThesisTransactions of the Charles S. Peirce Society 41 (2). 2005.
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71In defense of the Neyman-Pearson theory of confidence intervalsPhilosophy of Science 48 (2): 269-280. 1981.In Philosophical Problems of Statistical Inference, Seidenfeld argues that the Neyman-Pearson (NP) theory of confidence intervals is inadequate for a theory of inductive inference because, for a given situation, the 'best' NP confidence interval, [CIλ], sometimes yields intervals which are trivial (i.e., tautologous). I argue that (1) Seidenfeld's criticism of trivial intervals is based upon illegitimately interpreting confidence levels as measures of final precision; (2) for the situation which…Read more
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56Error and the growth of experimental knowledgeInternational Studies in the Philosophy of Science 15 (1): 455-459. 1996.
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