Modeling scientific evidence: the challenge of specifying likelihoods.
Evidence is an objective matter. This is the prevailing view within science, and confirmation theory should aim to capture the objective nature of scientific evidence. Modeling an objective evidence relation in a probabilistic framework faces two challenges: the probabilities must have the right epistemic foundation, and they must be specifiable given the hypotheses and data under consideration. Here I will explore how Sober's (2008, 2009) approach to confirmation handles these challenges of foundation and specification. In particular, I will argue that the specification problem proves especially difficult, and undermines the law of likelihood as an adequate representation of the objective nature of scientific evidence.
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