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Epistemic Probabilities are Degrees of Support, not Degrees of (Rational) Belief

Climenhaga, Nevin (2023) Epistemic Probabilities are Degrees of Support, not Degrees of (Rational) Belief. Philosophy and Phenomenological Research.

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Abstract

I argue that when we use ‘probability’ language in epistemic contexts—e.g., when we ask how probable some hypothesis is, given the evidence available to us—we are talking about degrees of support, rather than degrees of belief. The epistemic probability of A given B is the mind-independent degree to which B supports A, not the degree to which someone with B as their evidence believes A, or the degree to which someone would or should believe A if they had B as their evidence. My central argument is that the degree-of-support interpretation lets us better model good reasoning in certain cases involving old evidence. Degree-of-belief interpretations make the wrong predictions not only about whether old evidence confirms new hypotheses, but about the values of the probabilities that enter into Bayes’ Theorem when we calculate the probability of hypotheses conditional on old evidence and new background information.


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Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Climenhaga, Nevinnevin.climenhaga@acu.edu.au0000-0002-7376-8788
Keywords: Old evidence, Epistemic probability, Bayes' Theorem, Reasoning, Jeffrey conditionalization, Degrees of belief, Degrees of support
Subjects: Specific Sciences > Mathematics > Epistemology
General Issues > Confirmation/Induction
General Issues > Evidence
General Issues > Explanation
Specific Sciences > Probability/Statistics
General Issues > Theory/Observation
Depositing User: Nevin Climenhaga
Date Deposited: 03 Feb 2023 14:20
Last Modified: 03 Feb 2023 14:20
Item ID: 21713
Journal or Publication Title: Philosophy and Phenomenological Research
Official URL: https://onlinelibrary.wiley.com/doi/full/10.1111/p...
DOI or Unique Handle: 10.1111/phpr.12947
Subjects: Specific Sciences > Mathematics > Epistemology
General Issues > Confirmation/Induction
General Issues > Evidence
General Issues > Explanation
Specific Sciences > Probability/Statistics
General Issues > Theory/Observation
Date: January 2023
URI: https://philsci-archive.pitt.edu/id/eprint/21713

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