Pavitra comments on XKCD - Frequentist vs. Bayesians - Less Wrong Discussion
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Unfortunately, if there is disagreement merely about how much prior uncertainty is appropriate, then this is sufficient to render the outcome controversial.
I think your initial point is wrong.
There are 3 situations
You can get frequentism to work well by its own lights by throwing away information. The canonical example here would be the Mann-Whitney U test. Even if the prior info and data are both too sparse to indicate an adequate sampling distribution/data model, this test will still work (for frequentist values of "work").