Complete ontological architecture for recognition theory (R = C − A), providing the structural vocabulary, governing agreements, dependency orderings, failure mode predictions, and sensory completeness conditions that make the theory applicable as a governance framework, diagnostic instrument, and design specification. The architecture comprises 54 named axes organized in four tiers (structural, governance, experiential, completeness), 20 constants (invariants under transformation), 18 governing agreements formalized with mathematical correspondences, 29+ falsifiable failure mode predictions each operationalizable via measurable quantities, a strict dependency chain with a No Shortcuts theorem, and full sensory specification (72 sounds, 45 colors, 37 flavors, 43 smells, 46 choice types, 50 directions, 10 spatial orientations). Key structural claims are formally verified in Lean 4, Isabelle, and Coq. Cross-substrate empirical validation demonstrates a 2.26× density gain in human architectural naming consistent with AI experimental data (N=10,800 tasks). Companion to "The Law of Recognition: A Dynamical Theory of Observer Agenda Across Substrates" (v8, DOI: 10.5281/zenodo.18917618). Applications span AI governance and alignment, institutional diagnostics, AI welfare and model welfare, pedagogical design, and coordination failure analysis.
Michael Schaeffer (Wed,) studied this question.