Abstract
Several different Bayesian models of epistemic utilities (see, e.g., [37], [24], [40], [46]) have been used to explain why it is rational for scientists to perform experiments. In this paper, I argue that a model-suggested independently by Patrick Maher [40] and Graham Oddie [46]-that assigns epistemic utility to degrees of belief in hypotheses provides the most comprehensive explanation. This is because this proper scoring rule (PSR) model captures a wider range of scientifically acceptable attitudes toward epistemic risk than the other Bayesian models that have been proposed. I also argue, however, that even the PSR model places unreasonably tight restrictions on a scientist's attitude toward epistemic risk. As a result, such Bayesian models of epistemic utilities fail as normative accounts-not just as descriptive accounts (see, e.g., [31], [14])-of scientific inquiry.
Original language | English (US) |
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Pages (from-to) | 215-246 |
Number of pages | 32 |
Journal | Studia Logica |
Volume | 86 |
Issue number | 2 |
DOIs | |
State | Published - Jul 2007 |
Keywords
- Bayesianism
- Categorical belief
- Degrees of belief
- Epistemic risk
- Epistemic utility
- Proper scoring rule
- Scientific experiment
ASJC Scopus subject areas
- Logic
- History and Philosophy of Science