Constitutional Dynamics: A Research Programme for Testing Emergent Stability in Complex Governance Systems

The Constitutional Dynamics Series presents a three-layer research programme for investigating whether constitutional stability can emerge from local interaction rules in multi-agent governance systems, and for translating validated theoretical constructs into operational governance mechanisms. CD-1 (Theoretical Dynamics) introduces the Constitutional Lattice, a falsifiable computational framework in which agents are subject to oscillatory coupling, linear restoring forces toward a constitutional baseline, and ambient relational pressure. We report that the conjectured privileged coupling ratio Φ−1 ≈0.618 is not supported; settled variance decreased monotonically across the tested range with no distinguishing feature at Φ−1. Scaling tests reveal that minimum inter-agent separation decreases from 0.070 at N = 64 to 0.0023 at N = 1024, indicating that scale-invariant clustering prevention remains an open problem. CD-2 (Empirical Adjudication) establishes the methodological protocols for determining whether the theoretical constructs correspond to measurable institutional behaviour. The paper does not present empirical results but defines evidentiary criteria, proxy-variable development, preregistered falsification thresholds, and case selection protocols including adversarial cases. Three outcomes are possible: strong correspondence (validated constructs graduate to CD-3), partial correspondence (only validated concepts migrate), or no correspondence (CD-1 remains a theoretical model; CD-3 proceeds on governance evidence alone). CD-3 (Applied Governance) presents the Constitutional Compliance Mesh (CCM), a human-centred architecture for coordinating AI assurance across heterogenous institutional actors while preserving autonomy and accountability. The CCM is designed as an advisory system—it monitors, alerts, and recommends; it does not enforce. Every intervention requires human authorisation. The framework aligns with the UN Global Dialogue on AI Governance, the Australian Voluntary AI Safety Standard, and the WEF AI Global Alliance. Crucially, the CCM does not require the force law or any other CD-1 construct to be validated; it stands on governance evidence alone. The programme’s enduring contribution is methodological: a demonstration of how governance architectures can be evaluated with the same epistemic discipline expected of scientific theories—hypotheses explicit, validation criteria specified in advance, negative results reported, implementation assumptions disclosed, and unresolved questions left visible until empirically addressed.