And if I made this point in a non-political context - e.g., "you must account for the base rate for $disease when interpreting a $disease test" - no one would be disputing it.
If you or anyone else here can even present a (utilitarian) model where ignoring base rates leads to a better decision, by all means do it. I'd love to see this, though I suspect the actual outcome of such an effort will merely be the person attempting to do it gaining a much better understanding of Bayes rule.
And I do think that is fair, if there is not a simple way of actually measuring the utility and such (re your complaint about $diseases, medicine has at least somewhat reliable tests), all the stuff about the modeling is just theatrics.
Also, I now strongly recommend you go through the exercise I suggested. Then you'll realize that accurate tests do NOT somehow eliminate the need for models or accounting for base rates.
I'm reaching for the opposite point. Some sort of meaningful evaluation of actual outcomes is necessary to make utilitarian decisions. If the evaluation of the outcome is arbitrary, then so is the decision.
I mean, if you only talk to men and then measure where you derived utility, I'm not sure you've properly evaluated the model yet (if you interact with a certain percentage of women at conferences and keep track of all this in order to make sure that your model is working out properly, well then, more power to you).