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Is there a Bayesian justification of hypothetico-deductive inference?

Research output: Contribution to journalArticle

Original languageEnglish
Number of pages21
JournalNoûs
DOIs
DateAccepted/In press - 4 Jan 2019
DatePublished (current) - 30 Jan 2019

Abstract

Many philosophers have claimed that Bayesianism can provide a simple justification for hypothetico-deductive (H-D) inference, long regarded as a cornerstone of the scientific method. Following up a remark of van Fraassen (1985), we analyze a problem for the putative Bayesian justification of H-D inference in the case where what we learn from observation is logically stronger than what our theory implies. Firstly, we demonstrate that in such cases the simple Bayesian justification does not necessarily apply. Secondly, we identify a set of sufficient conditions for the mismatch in logical strength to be justifiably ignored as a "harmless idealization''. Thirdly, we argue, based upon scientific examples, that the pattern of H-D inference of which there is a ready Bayesian justification is only rarely the pattern that one actually finds at work in science. Whatever the other virtues of Bayesianism, the idea that it yields a simple justification of a pervasive pattern of scientific inference appears to have been oversold.

    Research areas

  • hypothetico-deductive inference, Bayesian confirmation theory

    Structured keywords

  • Centre for Science and Philosophy

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    Rights statement: This is the author accepted manuscript (AAM). The final published version (version of record) is available online via Wiley at https://doi.org/10.1111/nous.12277 . Please refer to any applicable terms of use of the publisher.

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