The issue is more the being stuck than the range: say it is (0.4, 0.6) rather than (0, 1), you’d still be inert. Vallinder (2018) discusses this extensively, including issues around infectiousness and generality.
You can entertain both a limited range for your prior probability, and a limited range of likelihood functions, and use closed (compact) sets if you’re away from 0 and 1 anyway. Surely you can update down from 0.6 if you had only one prior and likelihood, and if you can do so with your hardest to update distribution with 0.6, then this will reduce the right boundary.
The issue is more the being stuck than the range: say it is (0.4, 0.6) rather than (0, 1), you’d still be inert. Vallinder (2018) discusses this extensively, including issues around infectiousness and generality.
You can entertain both a limited range for your prior probability, and a limited range of likelihood functions, and use closed (compact) sets if you’re away from 0 and 1 anyway. Surely you can update down from 0.6 if you had only one prior and likelihood, and if you can do so with your hardest to update distribution with 0.6, then this will reduce the right boundary.