  In several papers, John Norton has argued that Bayesianism cannot handle
ignorance adequately due to its inability to distinguish between neutral and
disconfirming evidence. He argued that this inability sows confusion in, e.g.,
anthropic reasoning in cosmology or the Doomsday argument, by allowing one to
draw unwarranted conclusions from a lack of knowledge. Norton has suggested
criteria for a candidate for representation of neutral support. Imprecise
credences (families of credal probability functions) constitute a
Bayesian-friendly framework that allows us to avoid inadequate neutral priors
and better handle ignorance. The imprecise model generally agrees with Norton's
representation of ignorance but requires that his criterion of self-duality be
reformulated or abandoned.
