yes

OK. I agree with that insofar as agents having the same prior entails them having the same model.

aaahhh.... I changed the language of that sentence at least three times before settling on what you saw. Here's what I probably should have posted (and what I was going to post until the last minute):

There's no model checking because there is only one model - the correct model.

That is probably intuitively easier to grasp, but I think a bit inconsistent with my language in the rest of the post. The language is somewhat difficult here because our uncertainty is simultaneously a map and a territory.

Ah, I think I get you; a PB (perfect Bayesian) doesn't see a need to test their model because whatever specific proposition they're investigating implies a particular correct model.

For the record, I thought this sentence was perfectly clear. But I am a statistics grad student, so don't consider me representative.

Yeah, I figured you wouldn't have trouble with it since you talked about taking classes in this stuff - that footnote was intended for any lurkers who might be reading this. (I expected quite a few lurkers to be reading this given how often the Gelman and Shalizi paper's been linked here.)

Are you asserting that this a catch for my position? Or the "never look back" approach to priors? What you are saying seems to support my argument.

It's a catch for the latter, the PB. In reality most scientists typically don't have a wholly unambiguous proposition worked out that they're testing - or the proposition they are testing is actually not a good representation of the real situation.