Semantic Manifold Competence

Semantic Manifold Competence (SMC) proposes that intelligence is best understood not as a collection of separate cognitive faculties but as competence over semantic manifolds: the capacity to construct, maintain, navigate, transform, and govern structured meaning-bearing topologies while preserving coherence under novelty. The paper distinguishes a semantic manifold from an ordinary graph by its individuating feature — the admissible-transformation dynamics that determine which movements through meaning are lawful, rather than the inventory of nodes and edges itself. From this it develops operational accounts of local coherence, global coherence, and governance, and reinterprets the Turing Test as a measurement of semantic manifold competence rather than of imitation: successful participation reveals competence as a hidden variable. The framework is stated across three explicit registers — expository metaphor, central hypothesis, and testable content — with its empirical weight carried by predicted, observable failure modes (fragmentation, distortion, collapse, drift, governance failure, and attractor instability). SMC is offered as a theory of structured meaning dynamics, not a complete ontology of mind, and situates itself within a wider body of work on governed semantic representation, topology, and lexical identity.