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My shortform post yesterday about proposition negations, could I get some discussion on that? Please DM me if you like! I need to know if and where there's been good discussion about how Bayesian estimate tracking relates with negation! I need to know if I'm looking at it the wrong way!
The short answer is that if you have a set of mutually exclusive hypotheses, such as a proposition and its negation, then your credences for them should sum to unity. Conditional on MTBI's assumptions, a 55% credence for T-type does indeed imply a 45% credence for F-type. If I think people will misunderstand me due to connotations, then I need to be more clear when expressing myself, but that doesn't change my internal beliefs.
What sort of discussion are you looking for? Negation is fairly straightforward in classical propositional logic, predicate logic, and probability (the bases for Bayesian reasoning).
If questions about personality types are implicitly tied to some particular model, then the proposition "A has personality type X" really means "A has personality type X in model M", which in turn usually boils down to "A will have (or had) particular ranges of scores in M's associated personality test under the prescribed conditions for administering it".
How does negation come into such a discussion? Maybe you want to talk about the differences between negating various parts of that proposition versus negating the whole thing? I'm not sure.