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  1. The Duhemian Argument.Adolf Grünbaum - 1960 - Philosophy of Science 27 (1):75 - 87.
    This paper offers a refutation of P. Duhem's thesis that the falsifiability of an isolated empirical hypothesis H as an explanans is unavoidably inconclusive. Its central contentions are the following: 1. No general features of the logic of falsifiability can assure, for every isolated empirical hypothesis H and independently of the domain to which it pertains, that H can always be preserved as an explanans of any empirical findings O whatever by some modification of the auxiliary assumptions A in conjunction (...)
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  • Severe tests, arguing from error, and methodological underdetermination.Deborah G. Mayo - 1997 - Philosophical Studies 86 (3):243-266.
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  • Response to Howson and Laudan.Deborah G. Mayo - 1997 - Philosophy of Science 64 (2):323-333.
    A toast is due to one who slays Misguided followers of Bayes, And in their heart strikes fear and terror With probabilities of error! (E.L. Lehmann).
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  • Ducks, Rabbits, and Normal Science: Recasting the Kuhn’s-Eye View of Popper’s Demarcation of Science.Deborah G. Mayo - 1996 - British Journal for the Philosophy of Science 47 (2):271-290.
    Kuhn maintains that what marks the transition to a science is the ability to carry out ‘normal’ science—a practice he characterizes as abandoning the kind of testing that Popper lauds as the hallmark of science. Examining Kuhn's own contrast with Popper, I propose to recast Kuhnian normal science. Thus recast, it is seen to consist of severe and reliable tests of low-level experimental hypotheses (normal tests) and is, indeed, the place to look to demarcate science. While thereby vindicating Kuhn on (...)
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  • How about bust? Factoring explanatory power back into theory evaluation.Larry Laudan - 1997 - Philosophy of Science 64 (2):306-316.
    1. Introduction. The papers by Hellman and Mayo offer up a rich menu of problems and proposed solutions, so there is much here for a friendly critic to fasten on. In order to bring a modicum of focus to my commentary, I shall limit my remarks to the Duhem problem and its radiations in epistemology and methodology. Both Mayo and Hellman claim to have solutions to that hoary old problem and they tout these solutions as key indicators of the explanatory (...)
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  • A logic of induction.Colin Howson - 1997 - Philosophy of Science 64 (2):268-290.
    In this paper, I present a simple and straightforward logic of induction: a consequence relation characterized by a proof theory and a semantics. This system will be called LI. The premises will be restricted to, on the one hand, a set of empirical data and, on the other hand, a set of background generalizations. Among the consequences will be generalizations as well as singular statements, some of which may serve as predictions and explanations.
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  • The Duhem thesis.Roger Ariew - 1984 - British Journal for the Philosophy of Science 35 (4):313-325.
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  • (1 other version)La théorie physique: son objet et sa structure.P. Duhem - 1906 - Revue Philosophique de la France Et de l'Etranger 61:324-327.
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  • Duhem's problem, the bayesian way, and error statistics, or "what's belief got to do with it?".Deborah G. Mayo - 1997 - Philosophy of Science 64 (2):222-244.
    I argue that the Bayesian Way of reconstructing Duhem's problem fails to advance a solution to the problem of which of a group of hypotheses ought to be rejected or "blamed" when experiment disagrees with prediction. But scientists do regularly tackle and often enough solve Duhemian problems. When they do, they employ a logic and methodology which may be called error statistics. I discuss the key properties of this approach which enable it to split off the task of testing auxiliary (...)
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  • Error statistics and learning from error: Making a virtue of necessity.Deborah G. Mayo - 1997 - Philosophy of Science 64 (4):212.
    The error statistical account of testing uses statistical considerations, not to provide a measure of probability of hypotheses, but to model patterns of irregularity that are useful for controlling, distinguishing, and learning from errors. The aim of this paper is (1) to explain the main points of contrast between the error statistical and the subjective Bayesian approach and (2) to elucidate the key errors that underlie the central objection raised by Colin Howson at our PSA 96 Symposium.
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