Yablo, Stephen (2026) Fine-Grained Evidence. [Preprint]

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Abstract

Bayesian conditionalization is rigid: learning E fixes p(E) at 1 while preserving probabilities
conditional on E. Non-rigid update is preferable when, in the course of learning that E is true, we change
our views about how—by way of which truthmakers ϵ. A Jeffrey-style generalization of Bayes—active
conditioning—is developed which gives learning events a handle on p(ϵ|E) and p(E) both. E brings
a truthmaker-incorporating “probasition” to the table, rather than simply an intension. Confirmation
relations go hyperintensional as a result.

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Item Type:	Preprint
Creators:	Creators Email ORCID Yablo, Stephen yablo@mit.edu 0000-0002-9486-8323
Keywords:	probability, semantics, Bayesian epistemology, update, truthmakers, meaning, evidence, hyperintensionality
Subjects:	General Issues > Confirmation/Induction General Issues > Evidence Specific Sciences > Probability/Statistics General Issues > Theory Change
Depositing User:	Stephen Yablo
Date Deposited:	06 Jan 2026 19:17
Last Modified:	06 Jan 2026 19:17
Item ID:	27749
Subjects:	General Issues > Confirmation/Induction General Issues > Evidence Specific Sciences > Probability/Statistics General Issues > Theory Change
Date:	2026
URI:	https://philsci-archive.pitt.edu/id/eprint/27749

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