I agree up to the battlefield metaphor, most people aren’t hardcore frequentists or bayesians and don’t care about the any battle. I was in a philosophy of science conference this July and was accused of peddling “bayesian propaganda” because I said something along the lines of ‘bayesian inference is the natural approach to formulating a hierarchical inference problem’. His arguments was that up to the priors any inference problem you could set up in a bayesian way you could set up in a frequenstist framework, and it was because the former required a deeper understanding of inference that it endeded up being more sophisticated, not anything intrinsic to bayesianism.
I realize a lot of people will, but I’m not sure I even have a problem with the definition that bayesian statistics is simply one that uses bayes rule and therefore priors. If that’s the case, though, the flat-prior assumption makes frequentist inference a particular case of bayesian inference and the choice between them would require understanding the assumptions of either approach. It kind of boils down to “choose whatever you like, but be prepared to justify the implications”.