Vassend, Olav Benjamin (2018) A Verisimilitude Framework for Inductive Inference, with an Application to Phylogenetics. [Preprint]
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Abstract
Bayesianism and likelihoodism are two of the most important frameworks philosophers of science use to analyse scientific methodology. However, both frameworks face a serious objection: much scientific inquiry takes place in highly idealized frameworks where all the hypotheses are known to be false. Yet, both Bayesianism and likelihoodism seem to be based on the assumption that the goal of scientific inquiry is always truth rather than closeness to the truth. Here, I argue in favor of a verisimilitude framework for inductive inference. In the verisimilitude framework, scientific inquiry is conceived of, in part, as a process where inference methods ought to be calibrated to appropriate measures of closeness to the truth. To illustrate the verisimilitude framework, I offer a reconstruction of parsimony evaluations of scientific theories, and I give a reconstruction and extended analysis of the use of parsimony inference in phylogenetics. By recasting phylogenetic inference in the verisimilitude framework, it becomes possible to both raise and address objections to phylogenetic methods that rely on parsimony.
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| Item Type: | Preprint | ||||||
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| Additional Information: | Accepted by the British Journal for the Philosophy of Science | ||||||
| Keywords: | Bayesian inference, verisimilitude, inductive inference | ||||||
| Subjects: | General Issues > Confirmation/Induction General Issues > Models and Idealization Specific Sciences > Probability/Statistics |
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| Depositing User: | Olav Vassend | ||||||
| Date Deposited: | 20 Jun 2018 17:56 | ||||||
| Last Modified: | 20 Jun 2018 17:56 | ||||||
| Item ID: | 14788 | ||||||
| Subjects: | General Issues > Confirmation/Induction General Issues > Models and Idealization Specific Sciences > Probability/Statistics |
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| Date: | 2018 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/14788 |
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