You're right in the sense that the formula doesn't provide just how well that event supports, reconciles with, a particular hypothesis -- it also provides how well the event supports or reconciles with a different hypothesis.
No.
The comparative semantics of the likelihood ratio is not just a handy add-on feature; it's a requirement of the method. This is especially acute in your model because you were shown how your formulation is a false dilemma. H/~H is the wrong formulation because ~H is not actually a hypothesis but rather a catch-all category of everything -- no matter how contradictory -- that isn't materialism. As such, not all of ~H can ever be simultaneously true. You once gave lip-service to that concept, but now it seems you've forgotten it again and must be reminded of it.
Further, you propose to render your conclusion solely on the basis of having computed P(H|E) without doing anything to look at P(K|E), where K is whatever flavor of immortality you're trying to prove. Without a credible story for reckoning P(E|K) you can't conclude -- having done only half the work -- that P(H|E) < P(K|E). And you can't do anything with P(~H|E) without any sort of piecewise formulation because of your false dilemma.
But then, both H and ~H accept P(a) as being 1.00...
No.
There is a difference between reckoning some P(x|
h)
as if some arbitrary
h were true, and the actual P(
h). Accepting
h arguendo is not tantamount to saying P(
h) = 1. You're mixing and matching dissimilar concepts from different parts of the inference process.
the prior probability of ~H, and the likelihood of E|~H are not affected by ~H's inclusion of a...
If you want to factor out the physical brain, in the broken way you're suggesting, then you'd be left with the notion that P(H) = 1 and P(~H) = P(
b), where
b is whatever "something else" your pet theory K would require. Even if P(
b) = 1 you couldn't argue that K were more probable than H, only -- at best -- that it was equally probable.
But since all this conflates priors with likelihoods, it's all moot anyway. You once confessed you didn't really understand how the Bayesian formulations arrived at their values. Perhaps now is the time to own the consequences of that confession rather than bluster your way through this ongoing nonsense.