A causal Bayes net analysis of dispositions

Synthese 198 (5):4873-4895 (2021)
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Abstract

In this paper we develop an analysis of dispositions by means of causal Bayes nets. In particular, we analyze dispositions as cause-effect structures that increase the probability of the manifestation when the stimulus is brought about by intervention in certain circumstances. We then highlight several advantages of our analysis and how it can handle problems arising for classical analyses of dispositions such as masks, mimickers, and finks.

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Author Profiles

Florian Fischer
Universität Siegen
Alexander Gebharter
Marche Polytechnic University

Citations of this work

A Refined Propensity Account for GRW Theory.Lorenzo Lorenzetti - 2021 - Foundations of Physics 51 (2):1-20.
On Dispositional Masks.Matthew Turyn - 2021 - Synthese 199 (5-6):11865-11886.

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