David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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In Ellery Eells & James H. Fetzer (eds.), The Place of Probability in Science. Springer 133--60 (2010)
Evolutionary theory is awash with probabilities. For example, natural selection is said to occur when there is variation in fitness, and fitness is standardly decomposed into two components, viability and fertility, each of which is understood probabilistically. With respect to viability, a fertilized egg is said to have a certain chance of surviving to reproductive age; with respect to fertility, an adult is said to have an expected number of offspring.1 There is more to evolutionary theory than the theory of natural selection, and here too one finds probabilistic concepts aplenty. When there is no selection, the theory of neutral evolution says that a gene’s chance of eventually reaching fixation is 1/(2N), where N is the number of organisms in the generation of the diploid population to which the gene belongs. The evolutionary consequences of mutation are likewise conceptualized in terms of the probability per unit time a gene has of changing from one state to another. The examples just mentioned are all “forwarddirected” probabilities; they describe the probability of later events, conditional on earlier events. However, evolutionary theory also uses “backwards probabilities” that describe the probability of a cause conditional on its effects; for example, coalescence theory allows one to calculate the expected number of generations in the past that the genes in the present generation find their most recent common ancestor.
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J. Butterfield (2011). Less is Different: Emergence and Reduction Reconciled. [REVIEW] Foundations of Physics 41 (6):1065-1135.
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Rachael Briggs (forthcoming). Foundations of Probability. Journal of Philosophical Logic:1-16.
Mauricio Suárez (2007). Quantum Propensities. Studies in History and Philosophy of Science Part B 38 (2):418-438.
Lane DesAutels (2015). Toward a Propensity Interpretation of Stochastic Mechanism for the Life Sciences. Synthese 192 (9):2921-2953.
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