Unified Mastery Meta-Theory (UMMT) is a domain-agnostic, axiomatic framework that integrates multiple foundational theories of mastery into a single coherent system. It defines mastery as a latent, multidimensional equilibrium state characterized by structural fidelity, counterfactual robustness, temporal stability, and epistemic identifiability under bounded observation. UMMT unifies representation, dynamics, inference limits, failure modes, and construct validity within a minimal set of axioms, deriving existing mastery frameworks as necessary consequences rather than independent assumptions. Presented at the meta-theoretical level, UMMT establishes normative boundaries on what can be inferred, stabilized, and validly claimed about mastery while deliberately deferring specific algorithms, metrics, and implementations.
Murad Ahmadov (Sat,) studied this question.