David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Dialectica 62 (4):525-533 (2008)
Although it has often been claimed that all the information contained in second-order probabilities can be contained in first-order probabilities, no practical recipe for the elimination of second-order probabilities without loss of information seems to have been presented. Here, such an elimination method is introduced for repeatable events. However, its application comes at the price of losses in cognitive realism. In spite of their technical eliminability, second-order probabilities are useful because they can provide models of important features of the world that are cognitively more plausible than those that can be obtained with single-level probabilities.
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Sven Ove Hansson (2009). Measuring Uncertainty. Studia Logica 93 (1):21 - 40.
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