David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Synthese 182 (3):413-432 (2010)
Some have argued that chance and determinism are compatible in order to account for the objectivity of probabilities in theories that are compatible with determinism, like Classical Statistical Mechanics (CSM) and Evolutionary Theory (ET). Contrarily, some have argued that chance and determinism are incompatible, and so such probabilities are subjective. In this paper, I argue that both of these positions are unsatisfactory. I argue that the probabilities of theories like CSM and ET are not chances, but also that they are not subjective probabilities either. Rather, they are a third type of probability, which I call counterfactual probability. The main distinguishing feature of counterfactual-probability is the role it plays in conveying important counterfactual information in explanations. This distinguishes counterfactual probability from chance as a second concept of objective probability.
|Keywords||Chance Determinism Probability concepts Objective probability Credence|
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References found in this work BETA
Daniel Kahneman, Paul Slovic & Amos Tversky (eds.) (1982). Judgment Under Uncertainty: Heuristics and Biases. Cambridge University Press.
Elliott Sober (1984). The Nature of Selection: Evolutionary Theory in Philosophical Focus. University of Chicago Press.
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Alan Hájek (2003). What Conditional Probability Could Not Be. Synthese 137 (3):273--323.
Citations of this work BETA
Rachael Briggs (forthcoming). Foundations of Probability. Journal of Philosophical Logic:1-16.
Roman Frigg & Carl Hoefer (2015). The Best Humean System for Statistical Mechanics. Erkenntnis 80 (3):551-574.
Lane DesAutels (2015). Toward a Propensity Interpretation of Stochastic Mechanism for the Life Sciences. Synthese 192 (9):2921-2953.
Marshall Abrams (2015). Probability and Manipulation: Evolution and Simulation in Applied Population Genetics. Erkenntnis 80 (S3):519-549.
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