ISO 639:2023 represents a unified standard for language identification, elevating languagecodes to semantic, contextual constructs1. This paper extends that foundation by formalizingrecursive semantic anchoring: a framework wherein each language entity χ is associated witha recursive identity operator φnm that captures semantic drift as a fixed-point transformation.We define φnm(χ) = χ ⊕ ∆(χ), where ∆(χ) is the semantic drift vector of χ. The base caseφ00 yields the canonical language identity, while φ99 9 represents the maximal drift state trigger-ing fallback to an anchor identity. We prove that for any language entity, iterative drift viaφ converges to a recoverable fixed point (semantic anchor) under mild conditions. Categoricalmorphism models are introduced, treating φnm as morphisms and drift deltas as arrows in acategory of languages. A functor Φ : DriftLang → AnchorLang maps each drifted languageobject to its anchored identity, ensuring consistency across transformations. We present a typol-ogy of semantic drift (axial, layered, hybrid) and encode the model in an RDF/Turtle schema(classes BaseLanguage, DriftedLanguage, ResolvedAnchor; properties phiIndex, hasDrift,isFallbackOf, etc.). Worked examples include disambiguation of Mandarin Chinese φ84 vs. aregional variant φ87 ⊂ φ84, and resolution of Nigerian Pidgin English via a shared English an-chor. Evaluation with transformer-based AI systems demonstrates improved language identityresolution under partial or noisy data, using φ-index thresholds for dynamic fallback routing.The proposed recursive φnm model is fully compatible with ISO/TC 37 principles, providing anAI-ready, self-contained symbolic system for representing language identity under drift, muta-tion, and translation. All formal claims are grounded in symbolic derivations, and the Appendixincludes comprehensive RDF examples, φ-trace logic, and proof sketches. Permanently archived on Arweave to secure intellectual provenance and prevent unacknowledged adaptation in academic publications, corporate use, or derivative technologies. https://arweave.net/yOTwOG9dEjg0P99qVVHmgQDnw3vsFawhe4IlxmPeEPM