Mechanized Foundations of Structural Governance: Machine-Checked Proofs for Governed Intelligence
Not on the map. Why?
Abstract (arXiv)
We present five results in the theory of structural governance for cognitive workflow systems. Three are mechanized in Coq 8.19 using the Interaction Trees library with parameterized coinduction; two are proved on paper with explicit reductions. The Coinductive Safety Predicate (gov_safe) is a coinductive property that captures governance safety for infinite program behaviors, indexed by a boolean permission flag that is provably false for ungoverned I/O and true for governed interpretations (mechanized). The Governance Invariance Theorem establishes that governance is uniform across the meta-recursive tower: governance at level n+1 reduces to governance at level n by definitional equality of the type (mechanized). The Sufficiency Theorem proves that four atomic primitives (code, reason, memory, call) are expressively complete for any discrete intelligent system, formalized as compositional closure of a Kleisli category (mechanized). The Alternating Normal Form provides a canonical decomposition of any machine into alternating code and effect layers, with a confluent rewriting system (paper proof). The Necessity Theorem proves via explicit reduction to Rice's theorem that an architecturally opaque component (the reason primitive) is mathematically necessary for problems requiring semantic judgment (paper proof). A sixth contribution connects the abstract model to the deployed runtime: the Verified Interpreter Specification formalizes the BEAM runtime's trust, capability, and hash chain logic in Coq, then tests the running system against this specification using property-based testing with over 70,000 randomly generated directive sequences and zero disagreements. The mechanization comprises approximately 12,000 lines across 36 modules with 454 theorems and zero admitted lemmas.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 5 of its 42 references that are in the map. First posted on arXiv 30 Apr 2026.
Builds on
5 of 42 references.
References · 5
- 2022Training language models to follow instructions with human feedbackcited by 15,971
- 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
- 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,651
- 2023NeMo Guardrails: A Toolkit for Controllable and Safe LLM Applications with Programmable Railscited by 365
- 2019Interaction Trees: Representing Recursive and Impure Programs in Coqcited by 7
Built on by
Citing papers per year: 2026: 5.
5 papers.
- 2026Effect-Transparent Governance for AI Workflow Architectures: Semantic Preservation, Expressive Minimality, and Decidability Boundariescited by 1
- 2026Algebraic Semantics of Governed Execution: Monoidal Categories, Effect Algebras, and Coterminous Boundariescited by 1
- 2026Certified Purity for Cognitive Workflow Executors: From Static Analysis to Cryptographic Attestationcited by 1
- 2026Cryptographic Registry Provenance: Structural Defense Against Dependency Confusion in AI Package Ecosystemscited by 1
- 2026Governed Metaprogramming for Intelligent Systems: Reclassifying Eval as a Governed Effectcited by 0
- 2026Governed Metaprogramming for Intelligent Systems: Reclassifying Eval as a Governed Effect5 May 2026
- 2026Cryptographic Registry Provenance: Structural Defense Against Dependency Confusion in AI Package Ecosystems5 May 2026
- 2026Certified Purity for Cognitive Workflow Executors: From Static Analysis to Cryptographic Attestation1 May 2026
- 2026Algebraic Semantics of Governed Execution: Monoidal Categories, Effect Algebras, and Coterminous Boundaries1 May 2026
- 2026Effect-Transparent Governance for AI Workflow Architectures: Semantic Preservation, Expressive Minimality, and Decidability Boundaries1 May 2026