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Goals and the Informativeness of Prior Probabilities

Vassend, Olav Benjamin (2017) Goals and the Informativeness of Prior Probabilities. [Preprint]

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Abstract

I argue that information is a goal-relative concept for Bayesians. More precisely, I argue that how much information (or confirmation) is provided by a piece of evidence depends on whether the goal is to learn the truth or to rank actions by their expected utility, and that different confirmation measures should therefore be used in different contexts. I then show how information measures may reasonably be derived from confirmation measures, and I show how to derive goal-relative non-informative and informative priors given background information. Finally, I argue that my arguments have important implications for both objective and subjective Bayesianism. In particular, the Uniqueness Thesis is either false or must be modified. Moreover, objective Bayesians must concede that pragmatic factors systematically influence which priors are rational, and subjective Bayesians must concede that pragmatic factors sometimes partly determine which prior distribution most accurately represents an agent's epistemic state.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Vassend, Olav Benjaminvassend@ntu.edu.sg
Keywords: Bayesian confirmation; Shannon information; Bayesianism; information measures; problem of the priors
Subjects: General Issues > Confirmation/Induction
General Issues > Decision Theory
Specific Sciences > Probability/Statistics
Depositing User: Olav Vassend
Date Deposited: 04 Aug 2017 15:18
Last Modified: 04 Aug 2017 15:18
Item ID: 13302
Official URL: https://link.springer.com/article/10.1007/s10670-0...
DOI or Unique Handle: https://doi.org/10.1007/s10670-017-9907-1
Subjects: General Issues > Confirmation/Induction
General Issues > Decision Theory
Specific Sciences > Probability/Statistics
Date: 6 June 2017
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/13302

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