Bayesian confirmation theories that incorporate idealizations

Philosophy of Science 68 (1):36-52 (2001)
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Abstract

Following Nancy Cartwright and others, I suggest that most theories incorporate, or depend on, one or more idealizing assumptions. I then argue that such theories ought to be regimented as counterfactuals, the antecedents of which are simplifying assumptions. If this account of the logical form of theories is granted, then a serious problem arises for Bayesians concerning the prior probabilities of theories that have counterfactual form. If no such probabilities can be assigned, then posterior probabilities will be undefined, as the latter are defined in terms of the former. I argue here that the most plausible attempts to address the problem of probabilities of conditionals fail to help Bayesians, and, hence, that Bayesians are faced with a new problem. In so far as these proposed solutions fail, I argue that Bayesians must give up Bayesianism or accept the counterintuitive view that no theories that incorporate any idealizations have ever really been confirmed to any extent whatsoever. Moreover, as it appears that the latter horn of this dilemma is highly implausible, we are left with the conclusion that Bayesianism should be rejected, at least as it stands.

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Michael Shaffer
Gustavus Adolphus College

Citations of this work

Ceteris Paribus Conditionals and Comparative Normalcy.Martin Smith - 2006 - Journal of Philosophical Logic 36 (1):97-121.
Counterfactuals and Scientific Realism.Michael J. Shaffer - 2012 - London and Basingstoke: Palgrave MacMillan.
Justifying the Norms of Inductive Inference.Olav Benjamin Vassend - 2022 - British Journal for the Philosophy of Science 73 (1):135-160.

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