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Bayesian Networks and the Problem of Unreliable Instruments
Published online by Cambridge University Press: 01 January 2022
Abstract
We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments. In particular, we consider (i) repeated measurements of a single test consequence of the hypothesis, (ii) measurements of multiple test consequences of the hypothesis, (iii) theoretical support for the reliability of the instrument, and (iv) calibration procedures. We evaluate these strategies on their relative merits under idealized conditions and show some surprising repercussions on the variety-of-evidence thesis and the Duhem-Quine thesis.
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- Copyright © The Philosophy of Science Association
Footnotes
We are grateful for comments from J. McKenzie Alexander, David R. Cox, Robert Dodier, Malcolm Forster, Branden Fitelson, Allan Franklin, Patrick Maher, Iain Martel, František Matuš, Theo Kuipers, Richard Scheines, Kent Staley and an anonymous referee of this journal. The research was supported by the Alexander von Humboldt Foundation, the Federal Ministry of Education and Research, and the Program for Investment in the Future (ZIP) of the German Government, by the National Science Foundation, Science and Technology Studies (SES 00-80580) and by the Transcoop Program and the Feodor Lynen Program of the Alexander von Humboldt Foundation. Stephan Hartmann also thanks Jim Lennox and the Center for Philosophy of Science at the University of Pittsburgh for their hospitality.
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