Journal of Philosophical Logic 41 (6):983-999 (2012)

Authors
Katie Steele
Australian National University
Abstract
This paper considers a special case of belief updating—when an agent learns testimonial data, or in other words, the beliefs of others on some issue. The interest in this case is twofold: (1) the linear averaging method for updating on testimony is somewhat popular in epistemology circles, and it is important to assess its normative acceptability, and (2) this facilitates a more general investigation of what it means/requires for an updating method to have a suitable Bayesian representation (taken here as the normative standard). The paper initially defends linear averaging against Bayesian-compatibility concerns raised by Bradley (Soc Choice Welf 29:609-632, 2007), as well as problems associated with multiple testimony updates. The resolution of these issues, however, requires an extremely nuanced interpretation of the parameters of the linear averaging model—the so-called weights of respect. We go on to propose a role that the parameters of any 'shortcut' updating function should play, by way of minimal interpretation of these parameters. The class of updating functions that is consistent with this role, however, excludes linear averaging, at least in its standard form
Keywords Testimony  Linear pooling  Bayesian belief change
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DOI 10.1007/s10992-012-9227-5
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References found in this work BETA

Epistemology of Disagreement: The Good News.David Christensen - 2007 - Philosophical Review 116 (2):187-217.
Reflection and Disagreement.Adam Elga - 2007 - Noûs 41 (3):478–502.
The Epistemic Significance of Disagreement.Thomas Kelly - 2005 - In John Hawthorne & Tamar Gendler (eds.), Oxford Studies in Epistemology, Volume 1. Oxford University Press. pp. 167-196.

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Citations of this work BETA

Policymaking Under Scientific Uncertainty.Joe Roussos - 2020 - Dissertation, London School of Economics
Support for Geometric Pooling.Jean Baccelli & Rush T. Stewart - forthcoming - Review of Symbolic Logic:1-40.

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