Bayesian Defenses of the Survival Hypothesis

Abstract

In the prior chapter, I explored two foundational Bayesian analyses of the empirical case for survival based largely on the data of mediumship. Broad and Dodds each argued that the posterior probability of the hypothesis of personal survival relative to this evidence is not greater than ½. In this chapter, I consider Bayesian defenses of the case for survival, especially Bayesian maneuvers designed to answer the skeptical concerns introduced in the prior chapter. After a detailed examination of C.J. Ducasse’s foundational study, I consider a recent cumulative case survival argument presented by R.W.K. Paterson. These survivalist arguments highlight the significance of two “traditional challenges”: (i) the contention that the prior probability of the survival hypothesis is low (what I will call “the prior probability challenge”), and (ii) there is some rival hypothesis that leads us to expect the evidence at least as well as the survival hypothesis (what is called the “counter-explanation challenge”). However, I argue that the traditional debate, focused as it has been on (i) and (ii), has been blind to a more fundamental conceptual issue in the logic of survival arguments, namely the reliance on auxiliary assumptions to generate well-defined likelihoods. Consequently, survivalists have tended to mask rather than engage the more fundamental problems that face empirical arguments for survival. I provide a preliminary exploration of this issue here, and I develop it and its implications for the traditional challenges more fully in the remaining chapters.