Calibration for epistemic causality

Erkenntnis 86 (4):941-960 (2021)
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Abstract

The epistemic theory of causality is analogous to epistemic theories of probability. Most proponents of epistemic probability would argue that one's degrees of belief should be calibrated to chances, insofar as one has evidence of chances. The question arises as to whether causal beliefs should satisfy an analogous calibration norm. In this paper, I formulate a particular version of a norm requiring calibration to chances and argue that this norm is the most fundamental evidential norm for epistemic probability. I then develop an analogous calibration norm for epistemic causality, argue that it is the *only* evidential norm required for epistemic causality, and show how an epistemic account of causality that incorporates this norm can be used to analyse objective causal relationships.

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Jon Williamson
University of Kent

Citations of this work

Applying Evidential Pluralism to the Social Sciences.Yafeng Shan & Jon Williamson - 2021 - European Journal for Philosophy of Science 11 (4):1-27.
The Principal Principle and subjective Bayesianism.Christian Wallmann & Jon Williamson - 2019 - European Journal for Philosophy of Science 10 (1):1-14.
The Principal Principle and subjective Bayesianism.Christian Wallmann & Jon Williamson - 2019 - European Journal for Philosophy of Science 10 (1):1-14.
Direct inference and probabilistic accounts of induction.Jon Williamson - 2023 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 54 (3):451-472.

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References found in this work

Knowledge and its limits.Timothy Williamson - 2000 - New York: Oxford University Press.
Accuracy and the Laws of Credence.Richard Pettigrew - 2016 - New York, NY.: Oxford University Press UK.
The Dappled World: A Study of the Boundaries of Science.Nancy Cartwright - 1999 - New York, NY: Cambridge University Press.
Thinking about mechanisms.Peter Machamer, Lindley Darden & Carl F. Craver - 2000 - Philosophy of Science 67 (1):1-25.
Knowledge and Its Limits.Timothy Williamson - 2000 - Philosophy 76 (297):460-464.

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