If for each of these observations P( observation | UAP ) is strictly greater than 0, then I suspect P(UAP) will go towards 1, monotonously, as the number of observations increases.
No. This violates the law of conservation of expected evidence. The relevant question is whether P( observation | UAP ) is bigger or smaller than P( observation | ~UAP ).
The problem, as I mentioned above, is that it's hard to estimate P( observation | UAP ).
What if we have n observations where P( observation | ~UAP ) through investigation has been found to be 0 and, while hard to determine, P( observation | UAP ) is reasonably said to be strictly greater than 0.
Then P(UAP) will go towards 1, monotonously, as the number of observations increases, right?
It would be a powerful tool to be able to dismiss fringe phenomena, prior to empirical investigation, on firm epistemological ground.
Thus I have elaborated on the possibility of doing so using Bayes, and this is my result:
Using Bayes to dismiss fringe phenomena
What do you think of it?