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Epistemic Theories of Objective Chance

Johns, Richard (2018) Epistemic Theories of Objective Chance. [Preprint]

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Abstract

Epistemic theories of objective chance hold that chances are idealised epistemic probabilities of some sort. After giving a brief history of this approach to objective chance, I argue for a particular version of this view, that the chance of an event E is its epistemic probability, given maximal knowledge of the possible causes of E. The main argument for this view is the demonstration that it entails all of the commonly-accepted properties of chance. For example, this analysis entails that chances supervene on the physical facts, that the chance function is an expert probability, that the existence of stable frequencies results from invariant chances in repeated experiments, and that chances are probably close to long-run relative frequencies in repeated experiments. Despite these virtues, the epistemic approach to chance have been neglected in recent decades, on account of their conflict with accepted views about closely related topics such as causation, laws of nature, and epistemic probability. However, existing views on these topics are also very problematic, and I believe that the epistemic view of chance is a key piece of this puzzle that, once in place, allows all the other pieces to fit together into a new and coherent way. I also respond to some criticisms of the epistemic theory that I favour.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Johns, Richardold.johns@gmail.com0000-0002-4220-5835
Keywords: Chance; epistemic probability; causation; laws of nature; symmetry
Subjects: General Issues > Causation
General Issues > Determinism/Indeterminism
General Issues > Laws of Nature
Specific Sciences > Probability/Statistics
Depositing User: Dr Richard Johns
Date Deposited: 07 Feb 2018 16:52
Last Modified: 07 Feb 2018 16:52
Item ID: 14356
DOI or Unique Handle: 10.1007/s11229-018-1719-6
Subjects: General Issues > Causation
General Issues > Determinism/Indeterminism
General Issues > Laws of Nature
Specific Sciences > Probability/Statistics
Date: 2018
URI: http://philsci-archive.pitt.edu/id/eprint/14356

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