Impersonal Probability as an Ideal Assessment Based on Accessible Evidence: A Viable Construct?

When risk analysts and others refer to the "true" probability of an event, it is not easy to give it a meaning which is sound and useful as a communication device for regulatory, research planning, and related purposes. An interpretation is herein offered which, unlike Bayesian probability, is impersonal and does not depend on a particular assessor; unlike Carnap's "logical" probability, it does not depend on information actually to hand. It is a generalization of frequency and propensity interpretations of impersonal probability applicable to unique events: an ideal assessment based on currently accessible (not in general "perfect") evidence. The argument is illustrated from decision-aiding experience which motivated the enquiry. Copyright 1993 by Kluwer Academic Publishers