Conflating - yes, hell-yes, I am simplifying as much as possible. I do use steps #4 and #5 within the predictive model including uncertainty estimates. My step frequentist 4 refers to this. The steps aren't completely aligned.
My comment is a description of the difference as it affects me, and not necessarily capturing all of the effects on others. Please do expand...
I suppose to me it's more of a difference of decision-theoretic approaches, which come up with decision rules that make "best" decisions given the data, under certain definitions of "best", versus descriptive-statistics approaches, which aim to summarize the data, test hypotheses, report significant correlations, etc. I can buy many of the arguments for decision-theoretic approaches (especially if you are in fact making decisions), but that doesn't necessarily tell me why I should use a specifically Bayesian decision-theoretic approach.
My comment is a description of the difference as it affects me, and not necessarily capturing all of the effects on others. Please do expand...