I understand the concern, but I’m hoping that as claims about the future are explicit and distinguished from conditional claims, this might not be a problem. That is, if the user has already set P(Trump nominated) = 0.01 and P(Trump president) = 0.009, they will be satisfied with having rejected the claims, and will be able to consider that P(Trump is president | Trump was nominated) = 0.8, in isolation. Also, the conditional P(Trump was nominated | Trump is president) is obviously almost 1, and that should prevent anyone from setting P(Trump is president | Trump was nominated) too low. Also, P(Trump nominated) and P(Trump president) should always have reasonable values on prediction markets, which would set some reasonable bounds on the conditionals.
More generally, I suspect that the Multiple-Stage Fallacy comes from confusing event probabilities with conditional probabilities, and ultimately, I believe that all problems and confusions can be solved with more rigour.
I understand the concern, but I’m hoping that as claims about the future are explicit and distinguished from conditional claims, this might not be a problem. That is, if the user has already set P(Trump nominated) = 0.01 and P(Trump president) = 0.009, they will be satisfied with having rejected the claims, and will be able to consider that P(Trump is president | Trump was nominated) = 0.8, in isolation. Also, the conditional P(Trump was nominated | Trump is president) is obviously almost 1, and that should prevent anyone from setting P(Trump is president | Trump was nominated) too low. Also, P(Trump nominated) and P(Trump president) should always have reasonable values on prediction markets, which would set some reasonable bounds on the conditionals.
More generally, I suspect that the Multiple-Stage Fallacy comes from confusing event probabilities with conditional probabilities, and ultimately, I believe that all problems and confusions can be solved with more rigour.