David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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British Journal for the Philosophy of Science 57 (1):197-218 (2006)
Daniel Hausman and James Woodward claim to prove that the causal Markov condition, so important to Bayes-nets methods for causal inference, is the ‘flip side’ of an important metaphysical fact about causation—that causes can be used to manipulate their effects. This paper disagrees. First, the premise of their proof does not demand that causes can be used to manipulate their effects but rather that if a relation passes a certain specific kind of test, it is causal. Second, the proof is invalid. Third, the kind of testability they require can easily be had without the causal Markov condition. Introduction Earlier views: manipulability v testability Increasingly weaker theses The proof is invalid MOD* is implausible Two alternative claims and their defects A true claim and a valid argument Indeterminism Overall conclusion.
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Citations of this work BETA
Frederick Eberhardt (2009). Introduction to the Epistemology of Causation. Philosophy Compass 4 (6):913-925.
Holly Andersen (2013). When to Expect Violations of Causal Faithfulness and Why It Matters. Philosophy of Science (5):672-683.
Frederick Eberhardt & Richard Scheines (2007). Interventions and Causal Inference. Philosophy of Science 74 (5):981-995.
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