Eder, Anna-Maria A. (2019) Evidential Probabilities and Credences. The British Journal for the Philosophy of Science. ISSN 1464-3537
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Abstract
Enjoying great popularity in decision theory, epistemology, and philosophy of science, Bayesianism as understood here is fundamentally concerned with epistemically ideal rationality. It assumes a tight connection between evidential probability and ideally rational credence, and usually interprets evidential probability in terms of such credence. Timothy Williamson challenges Bayesianism by arguing that evidential probabilities cannot be adequately interpreted as the credences of an ideal agent. From this and his assumption that evidential probabilities cannot be interpreted as the actual credences of human agents either, he concludes that no interpretation of evidential probabilities in terms of credence is adequate. I argue to the contrary. My overarching aim is to show on behalf of Bayesians how one can still interpret evidential probabilities in terms of ideally rational credence and how one can maintain a tight connection between evidential probabilities and ideally rational credence even if the former cannot be interpreted in terms of the latter. By achieving this aim I illuminate the limits and prospects of Bayesianism.
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| Item Type: | Published Article or Volume | ||||||
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| Keywords: | Bayesianism, Ideally Rational Credences, Epistemically Ideal Agents | ||||||
| Subjects: | General Issues > Confirmation/Induction General Issues > Evidence General Issues > Models and Idealization Specific Sciences > Probability/Statistics |
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| Depositing User: | Dr. Anna-Maria Eder | ||||||
| Date Deposited: | 27 Sep 2019 18:12 | ||||||
| Last Modified: | 27 Sep 2019 18:12 | ||||||
| Item ID: | 16460 | ||||||
| Journal or Publication Title: | The British Journal for the Philosophy of Science | ||||||
| Publisher: | Oxford University Press | ||||||
| Subjects: | General Issues > Confirmation/Induction General Issues > Evidence General Issues > Models and Idealization Specific Sciences > Probability/Statistics |
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| Date: | 2019 | ||||||
| ISSN: | 1464-3537 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/16460 |
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