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The PC Algorithm and the Inference to Constitution

Casini, Lorenzo and Baumgartner, Michael (2020) The PC Algorithm and the Inference to Constitution. [Preprint]

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Abstract

Alexander Gebharter (2017) has proposed to use one of the best known Bayesian network (BN) causal discovery algorithms, PC, to identify the constitutive dependencies underwriting mechanistic explanations. His proposal assumes that mechanistic constitution behaves like deterministic direct causation, such that PC is directly applicable to mixed variable sets featuring both causal and constitutive dependencies. Gebharter claims that such mixed sets, under certain restrictions, comply with PC’s background assumptions. The aim of this paper is to show that Gebharter’s proposal incurs severe problems, ultimately rooted in the widespread non-compliance of mechanistic systems with PC’s assumptions. This casts severe doubts on the attempt to implicitly define constitution as a form of deterministic direct causation complying with PC’s assumptions.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Casini, Lorenzolorenzo.casini@unige.ch0000-0001-9891-7324
Baumgartner, Michaelmichael.baumgartner@uib.no
Additional Information: Forthcoming in the British Journal for the Philosophy of Science
Keywords: mechanistic explanation; constitution; causation; Bayesian network; supervenience; PC.
Subjects: General Issues > Causation
General Issues > Explanation
Depositing User: Dr. Lorenzo Casini
Date Deposited: 07 Jul 2020 02:11
Last Modified: 08 Jul 2020 02:59
Item ID: 17437
Subjects: General Issues > Causation
General Issues > Explanation
Date: 28 May 2020
URI: https://philsci-archive-dev.library.pitt.edu/id/eprint/17437

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