URB #518 — The Self-Defeating Theorem: 13 Fatal Arguments Against Bayesianism as a Complete Epistemology

Bayesian epistemology claims to be the normative theory of rational belief update: all rational agents should represent beliefs as probability distributions and update them via Bayes' theorem upon receiving evidence. We present 13 independent arguments demonstrating that Bayesianism is neither complete nor self-consistent as an epistemology. The arguments range from structural (priors are arbitrary, base rates are inapplicable, TRALSE probabilities are unrepresentable) to self-referential (Bayesianism was not founded by its own principles; Bayesianism requires intuition to function while claiming to replace it) to catastrophic (Black Swan underestimation, rare disease denial, prior dominance making near-perfect evidence irrelevant). The **Ultimate Argument** (Argument 13) synthesizes these into a self-defeat theorem: Bayesianism, as a system of rational belief formation, fails its own standards for the same reasons it claims to be necessary. TI Sigma's LCC replaces Bayesian credence as the coherence measure of belief systems, with TRALSE probability handling the cases Bayesianism structurally cannot.