bayes’ theorem makes us consider the likelihood of some event a happening given event b, and pits that against the likelihood of event a happening if event b didn’t happen
This is very much like
vorp, where we try to figure out how much
marginal impact (i.e.
counterfactual impact) a person has: we say what was the likelihood of x happening given person a was there, vs what would the likelihood have been of x happening if person a wasn’t there