[selectionbias]

My problem with the 'Bayes=rationality' type of argument is that it ignores context and isn't really a case for reporting Bayesian vs frequentist estimates. If I am a researcher publishing results then I have an audience who interpret my results. If my audience is Bayesian and accept my model then all I need to do is report sufficient statistics and they can make their own Bayesian inferences given their priors, or better yet, I can just post my whole dataset. The very reason we need to report things like credible sets or confidence intervals rather than just sufficient statistics is because audiences in the real world want summary stats that they can easily interpret and are transparent. The best approach to inference is one that is the most useful to audiences, and that depends on context and practicalities rather than on some underlying philosophy of subjective vs objective probabilities.