I don’t think you need the concept of evidence. In Bayesian probability, the concept of evidence is equivalent to the concept of truth; both in the sense that P(X|X) = 1, whatever you consider evidence is true, but also P(X) = 1 --> P(A /\ X) = P(A|X), you can consider true sentences as evidence without changing anything else.
Add to this that good rationalist practice is to never assume that anything is P(A) = 1, so that nothing is actually true or actually an evidence. You can do epistemology exclusively in the hypotethical: what happens if I consider this true? And then derive consequences.
I don’t think you need the concept of evidence. In Bayesian probability, the concept of evidence is equivalent to the concept of truth; both in the sense that P(X|X) = 1, whatever you consider evidence is true, but also P(X) = 1 --> P(A /\ X) = P(A|X), you can consider true sentences as evidence without changing anything else.
Add to this that good rationalist practice is to never assume that anything is P(A) = 1, so that nothing is actually true or actually an evidence. You can do epistemology exclusively in the hypotethical: what happens if I consider this true? And then derive consequences.
I don’t think this helps, but that’s because you can’t reason without any assumptions (e.g. axioms, prior beliefs, etc.).