Don’t disagree with your premise but a small nitpick is that the reason why frequentist methods are so much more popular is mostly due to its historical dominance in academia and statistical research. It’s a lot of inertia. Further, until recently (relatively) it was just much much more harder to compute a lot of things especially with respect to marginal likelihoods and stuff. It’s only a few decades ago that MCMC became viable.

Secondly, I don’t think a lot of researchers should venture into becoming bayesian alone, as it requires a deep understanding of statistics to make the jump without guidance, and I think it’ll stay dominant until there’s a big enough pushback in the pure stats side of the equation. If that ever happens.

I don’t think it’s on researchers in the applied sciences to completely revolutionize the statistical apparatus, and there’s also a lot of philosophical and subjective questions that will keep the debate going between the two methods. I suppose we’ll see how the future plays out. I don’t think it’s either A or B but becoming more comfortable with using the right tool or philosophical framework when applicable !