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Manipulation and the Causal Markov Condition

Published online by Cambridge University Press:  01 January 2022

Daniel Hausman  and
James Woodward
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Abstract

This paper explores the relationship between a manipulability conception of causation and the causal Markov condition (CM). We argue that violations of CM also violate widely shared expectations—implicit in the manipulability conception—having to do with the absence of spontaneous correlations. They also violate expectations concerning the connection between independence or dependence relationships in the presence and absence of interventions.

Type
Causation and Bayesian Networks
Information
Philosophy of Science , Volume 71 , Issue 5: Proceedings of the 2002 Biennial Meeting of The Philosophy of Science Association. Part II: Symposia Papers , December 2004 , pp. 846 - 856
Copyright
Copyright © 2004 by the Philosophy of Science Association

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References

Cartwright, Nancy (2002), “Against Modularity, the Causal Markov Condition and Any Link between the Two: Comments on Hausman and Woodward”, Against Modularity, the Causal Markov Condition and Any Link between the Two: Comments on Hausman and Woodward 53:411–453.Google Scholar
Gopnik, Alison, Glymour, Clark, Sobel, David, Schulz, Laura E., Kushnir, Tamar, and Danks, David (2004), “A Theory of Causal Learning in Children: Causal Maps and Bayes Nets”, A Theory of Causal Learning in Children: Causal Maps and Bayes Nets 111(1): 3–32.Google ScholarPubMed
Hausman, Daniel, and Woodward, James (1999), “Independence, Invariance, and the Causal Markov Condition”, Independence, Invariance, and the Causal Markov Condition 50:521–583.Google Scholar
Hitchcock, Christopher (2001), “A Tale of Two Effects”, A Tale of Two Effects 110:361–396.Google Scholar
Spirtes, Peter, Glymour, Clark, and Scheines, Richard (2000), Causation, Prediction, and Search, 2nd ed. New York: MIT Press.Google Scholar
Woodward, James (2003), Making Things Happen: A Theory of Causal Explanation. Oxford: Oxford University Press.Google Scholar