I am definitely not using the terms as they are used professionally (and certainly not a criticism of Bayesian methods in any way). It was an attempt to explai

I am definitely not using the terms as they are used professionally (and certainly not a criticism of Bayesian methods in any way). It was an attempt to explain in more lay terms how when p-hacking is performed on some dataset, the "findings" can rarely be applied to larger (or different) datasets due to the arbitrary criteria used to reject the parts of the data that aren't conducive to the selected outcome, since the rejection criteria were sort of custom-fit to that specific dataset. I agree with everything you said.