Roughly, frequentist confidence intervals, but not Bayesian credible intervals, have the following coverage guarantee: if you repeat the sampling and analysis procedure over and over, in the long-run, the confidence intervals produced cover the truth some percentage of the time corresponding to the confidence level. If I set a 95% confidence level, then in the limit, 95% of the intervals I generate will cover the truth.
Right. This is what my comment there was pointing out: in his very own example, physics, 95% CIs do not get you 95% coverage since when we look at particle physics's 95% CIs, they are too narrow. Just like his Bayesian's 95% credible intervals. So what's the point?
I suspect you're talking past one another, but maybe I'm missing something. I skimmed the paper you linked and intend to come back to it in a few weeks, when I am less busy, but based on skimming, I would expect the frequentist to say something like, "You're showing me a finite collection of 95% confidence intervals for which it is not the case that 95% of them cover the truth, but the claim is that in the long run, 95% of them will cover the truth. And the claim about the long run is a mathematical fact."
I can see having worries that this doesn'...
http://xkcd.com/1132/
Is this a fair representation of frequentists versus bayesians? I feel like every time the topic comes up, 'Bayesian statistics' is an applause light for me, and I'm not sure why I'm supposed to be applauding.