Epistemic Accuracy and Subjective Probability
speaker: Marcello D'Agostino (Università di Milano)abstract: De Finetti suggested that scoring rules — namely, loss functions by which a forecaster is virtually charged depending on the degree of inaccuracy of his predictions — could be employed also to provide a compelling argument for probabilism. However, De Finetti’s choice of a specific scoring rule for this purpose (Brier’s quadratic rule) appears somewhat arbitrary, and the general pragmatic flavour of the argument — which makes it a variant of the well-known “Dutch Book Theorem” — has been deemed unsuitable for an epistemic justification of probabilism. In this paper we suggest how Brier’s rule may be justified on epistemic grounds by means of a strategy that is different from the one usually adopted for this purpose (e.g., in Joyce 1998), taking advantage of a recent characterization result concerning distance functions between real-valued vectors (D’Agostino and Dardanoni 2009). D’Agostino M, Dardanoni V (2009) What’s so special about Euclidean distance? A characterization result with applications to mobility and spatial voting. Social Choice and Welfare, 33 (2): 211-233; doi: 10.1007s00355-008-0353-5. Joyce JM (1998) A non-pragmatic vindication of probabilism. Philosophy of Science 65(4):575–603.
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