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 2008).
|Titolo:||Epistemic accuracy and subjective probability|
|Settore Scientifico Disciplinare:||Settore M-FIL/02 - Logica e Filosofia della Scienza|
|Data di pubblicazione:||2010|
|Digital Object Identifier (DOI):||10.1007/978-90-481-3263-8_8|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|