David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophy of Science 74 (3):330-347 (2007)
Time series of macroscopic quantities that are aggregates of microscopic quantities, with unknown one‐many relations between macroscopic and microscopic states, are common in applied sciences, from economics to climate studies. When such time series of macroscopic quantities are claimed to be causal, the causal relations postulated are representable by a directed acyclic graph and associated probability distribution—sometimes called a dynamical Bayes net. Causal interpretations of such series imply claims that hypothetical manipulations of macroscopic variables have unambiguous effects on variables “downstream” in the graph, and such macroscopic variables may be predictably produced or altered even while particular microstates are not. This paper argues that such causal time series of macroscopic aggregates of microscopic processes are the appropriate model for mental causation.
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References found in this work BETA
James Woodward (2003). Making Things Happen: A Theory of Causal Explanation. Oxford University Press.
Thomas Nagel (1974). What is It Like to Be a Bat? Philosophical Review 83 (October):435-50.
Jaegwon Kim (1998). Mind in a Physical World: An Essay on the Mind-Body Problem and Mental Causation. MIT Press.
Jaegwon Kim (2005). Physicalism, or Something Near Enough. Princeton University Press.
John W. Bickle (2008). Psychoneural Reduction: The New Wave. A Bradford Book.
Citations of this work BETA
David Danks (forthcoming). Goal-Dependence in Ontology. Synthese:1-16.
Vera Hoffmann-Kolss (forthcoming). Of Brains and Planets: On a Causal Criterion for Mind-Brain Identities. Synthese:1-13.
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