The Adaptive Policy Coherence Framework (APCF): Diagnosing Structural Fragility in Livestock Traceability Under Adaptive Governance Conditions

This preprint introduces and applies the Adaptive Policy Coherence Framework (APCF), a governance-grade analytic framework designed to diagnose why surveillance, traceability, and outbreak-response policies frequently fail once deployed into real-world adaptive systems—despite being technically well designed. Across public health, agriculture, biosecurity, and environmental regulation, surveillance and traceability infrastructures are commonly justified on the premise that increased visibility enables earlier detection, more targeted intervention, and improved outcomes. APCF demonstrates that this premise routinely breaks down when detection is structurally coupled to asymmetric enforcement risk, opaque decision-making, and historically punitive outcomes. Under such conditions, increased visibility does not produce increased cooperation. It predictably produces delayed reporting, partial compliance, informal substitution, and strategic avoidance. The framework is applied diagnostically to proposed livestock traceability reforms in Canada. This application does not assess regulatory intent, legal authority, or technical system capacity. Instead, it examines whether the internal logic of expanded traceability remains coherent once deployed into an institutional environment shaped by prior enforcement practices, economic vulnerability among regulated actors, and accumulated institutional memory. The analysis identifies a clear structural failure mode: the proposed traceability changes increase informational exposure without proportionately reducing downstream enforcement risk or uncertainty. Under APCF, this configuration is unstable. Where detection has historically been associated with severe, irreversible, or poorly bounded consequences, rational actors adapt by minimizing visibility rather than increasing participation. In such settings, expanded traceability requirements risk degrading data reliability and outbreak detection effectiveness, even as formal surveillance coverage appears to increase. Crucially, APCF treats these outcomes not as implementation failures, cultural resistance, or misinformation effects, but as predictable system-level responses to misaligned incentives and governance structures. From this perspective, the primary risk of the proposed traceability reforms is not non-compliance per se, but the systematic displacement of activity into less visible, less reliable, and less governable channels—a result that directly undermines the stated objectives of early detection and effective outbreak response. Methodologically, APCF employs a mixed-evidence approach that distinguishes epistemic roles rather than collapsing all sources into a single hierarchy. Scientific literature constrains behavioral and institutional plausibility; regulatory texts establish stated policy assumptions; legal and historical records define enforcement precedent; stakeholder statements indicate adaptive response pathways; and media and social discourse function as indicators of perceived risk environments. This structured integration strengthens analytic rigor while avoiding both technocratic reductionism and evidentiary relativism. The contribution of this work is diagnostic rather than prescriptive. It demonstrates how surveillance and traceability policies can become structurally counterproductive when governance-level risk asymmetries are left unaddressed. While the case study focuses on livestock traceability under the authority of Canadian Food Inspection Agency, the identified failure mode generalizes across domains characterized by surveillance, enforcement, and asymmetric consequence. APCF is presented as a transferable analytic instrument for policymakers, regulators, and funders seeking to identify policy fragility before credibility, participation, and effectiveness are eroded. The framework is institution-agnostic and non-accusatory, focusing on structural alignment rather than attribution of intent or fault.