NDLI: Intervention, determinism, and the causal minimality condition

Content Provider	Springer Nature Link
Author	Zhang, Jiji Spirtes, Peter
Copyright Year	2010
Abstract	We clarify the status of the so-called causal minimality condition in the theory of causal Bayesian networks, which has received much attention in the recent literature on the epistemology of causation. In doing so, we argue that the condition is well motivated in the interventionist (or manipulability) account of causation, assuming the causal Markov condition which is essential to the semantics of causal Bayesian networks. Our argument has two parts. First, we show that the causal minimality condition, rather than an add-on methodological assumption of simplicity, necessarily follows from the substantive interventionist theses, provided that the actual probability distribution is strictly positive. Second, we demonstrate that the causal minimality condition can fail when the actual probability distribution is not positive, as is the case in the presence of deterministic relationships. But we argue that the interventionist account still entails a pragmatic justification of the causal minimality condition. Our argument in the second part exemplifies a general perspective that we think commendable: when evaluating methods for inferring causal structures and their underlying assumptions, it is relevant to consider how the inferred causal structure will be subsequently used for counterfactual reasoning.
Starting Page	335
Ending Page	347
Page Count	13
File Format	PDF
ISSN	00397857
Journal	Synthese
Volume Number	182
Issue Number	3
e-ISSN	15730964
Language	English
Publisher	Springer Netherlands
Publisher Date	2010-06-20
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Causation Causal Bayesian network Determinism Markov condition Intervention Probability Logic Philosophy of Science Philosophy of Language Metaphysics Epistemology
Content Type	Text
Resource Type	Article
Subject	Philosophy Social Sciences

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