The Likelihood Ratio Measure and the Logicality Requirement

Erkenntnis 87 (2):459-475 (2020)
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Abstract

What sort of evidence can confer the strongest support to a hypothesis? A natural answer is that the evidence entails the hypothesis. Roush (Tracking Truth: Knowledge, Evidence, and Science, Clarendon Press, Oxford, 2005) claims that the likelihood ratio measure of degree of incremental support can deliver this intuitively natural result, and regards it as unifying “[the] account of induction and deduction in the only way that makes sense” (p. 163). In this paper, we highlight a difficulty in the treatment of this case, and question the great significance that is attached to this measure and its alleged capacity to accommodate the logicality requirement. We contrast the likelihood ratio measure with other measures (such as the Kemeny–Oppenheim measure and the difference measure), and argue that problems still emerge in light of tensions with plausible requirements for confirmation measures more generally.

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References found in this work

Scientific reasoning: the Bayesian approach.Peter Urbach & Colin Howson - 1993 - Chicago: Open Court. Edited by Peter Urbach.
Logic of Statistical Inference.Ian Hacking - 1965 - Cambridge, England: Cambridge University Press.
Tracking truth: knowledge, evidence, and science.Sherrilyn Roush - 2005 - New York: Oxford University Press.

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