Sprenger, Jan (2016) Foundations for a Probabilistic Theory of Causal Strength. [Preprint]

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Abstract

This paper develops axiomatic foundations for a probabilistic-interventionist theory of causal strength. Transferring methods from Bayesian confirmation theory, I proceed in three steps: (1) I develop a framework for defining and comparing measures of causal strength; (2) I argue that no single measure can satisfy all natural constraints; (3) I prove two representation theorems for popular measures of causal strength: Pearl's causal effect measure and Eells' difference measure. In other words, I demonstrate these two measures can be derived from a set of plausible adequacy conditions. The paper concludes by sketching future research avenues.

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Item Type:	Preprint
Creators:	Creators Email ORCID Sprenger, Jan j.sprenger@uvt.nl
Subjects:	General Issues > Causation Specific Sciences > Computer Science General Issues > Confirmation/Induction General Issues > Explanation Specific Sciences > Probability/Statistics
Depositing User:	Jan Sprenger
Date Deposited:	25 Feb 2016 04:04
Last Modified:	25 Feb 2016 04:04
Item ID:	11927
Subjects:	General Issues > Causation Specific Sciences > Computer Science General Issues > Confirmation/Induction General Issues > Explanation Specific Sciences > Probability/Statistics
Date:	2016
URI:	https://philsci-archive.pitt.edu/id/eprint/11927

Available Versions of this Item

• Foundations for a Probabilistic Theory of Causal Strength. (deposited 25 Feb 2016 04:04) [Currently Displayed]
  • Foundations for a Probabilistic Theory of Causal Strength. (deposited 18 Nov 2016 19:43)
    • Foundations of a Probabilistic Theory of Causal Strength. (deposited 10 Nov 2017 16:38)

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