> Specifically, I think I got the math right but the example wrong (and I confused you too). Don't worry, I was much more confused before you came along :-). I

> Specifically, I think I got the math right but the example wrong (and I confused you too). Don't worry, I was much more confused before you came along :-). I also followed the math in the paper but didn't know what devastating contradiction for Bayesianism it was oh-so-darkly hinting at. I keep trying to describe what happens if e and h are both general, and bouncing off. Let's try a different assumption: e is the statement "the first person tested is consistent with smoking->cancer". And in fact, we just tested them, and they're a smoker and have cancer. So e is unambiguously true. And h is the hypothesis "smoking -> cancer". Then: - e is 1 - h has increased - h|e has increased, in fact it is 1 - h|~e has decreased h|e is tautologically true, once we have observed e. And h|~e is e->h, the amount to which this observation implies "smoking->cancer". Which seems odd, though I don't have an immediate intuition about how an observation is supposed to effect, not the hypothesis that it supports, but the implication between itself and that hypothesis. But maybe that's the darkly-hinted-at problem?