A good nutshell description of the type of Bayesianism that many LWers think correct is objective Bayesianism with critical rationalism-like underpinnings. Where recursive justification hits bottom is particularly relevant. On my cursory skim, Albert only seems to be addressing "subjective" Bayesianism which allows for any choice of prior.
It seems to think the problem of the priors does in Bayesianism :-(
Popper seems outdated. Rejecting induction completely is not very realistic.
In what way would the Popperian approach fail to fit the decision rule approach on page 19 of Bickel and Doksum?
It says a decision rule (their term) is a function of the sample space, mapping something like complete sets of possible data to things people do. (I think it needs to be complete sets of all your data to be applied to real world human decision making. They don't explain what they are talking about in the type of way I think is good and clear. I think that's due to having in mind different problems they are trying to solve than I have. We have different goals without even very much overlap. They both involve "decisions" but we mean different thin...
I have just rediscovered an article by Max Albert on my hard drive which I never got around to reading that might interest others on Less Wrong. You can find the article here. It is an argument against Bayesianism and for Critical Rationalism (of Karl Popper fame).
Abstract:
Any thoughts?