Epistemic justification has been widely accepted as both a gradational and relational notion. Given those properties, a natural thought is to take degrees of epistemic justification to be probabilities. In this paper, we present a simple Bayesian framework for justification. In the first part, after putting the model in an evidentialist form, we distinguish different senses of “being evidence for” and “confirming”. Next, we argue that this conception should accommodate the two relevant kinds of qualitative confirmation or evidential support. In (...) the second part of the paper, we discuss the claim that this view is unable to satisfy the modified version of the conjunction closure for beliefs in probabilistically independent propositions. We defend that the underlying assumption on which this objection depends leads to an improper reading of the concept of epistemic probability. After providing a better interpretation of it, we put forward a rationale, which is based on the notion of conditional uncertainty, in support of a more plausible and restricted version of the closure of justification under conjunction. (shrink)

‘Bayesian epistemology’ became an epistemological movement in the 20th century, though its two main features can be traced back to the eponymous Reverend Thomas Bayes (c. 1701-61). Those two features are: (1) the introduction of a formal apparatus for inductive logic; (2) the introduction of a pragmatic self-defeat test (as illustrated by Dutch Book Arguments) for epistemic rationality as a way of extending the justification of the laws of deductive logic to include a justification for the laws of inductive logic. (...) The formal apparatus itself has two main elements: the use of the laws of probability as coherence constraints on rational degrees of belief (or degrees of confidence) and the introduction of a rule of probabilistic inference, a rule or principle of conditionalization. (shrink)