The Adaptive Policy Coherence Framework (APCF): A Governance-Grade Analytic Framework for Policy Design Under Adaptive Behavior

Policy and regulatory frameworks are often designed under idealized assumptions: rational compliance, stable incentives, and linear responses to intervention. In practice, however, policy operates in complex adaptive environments where individuals, institutions, and markets respond strategically, substitute behaviors, exploit loopholes, or disengage entirely. These adaptive dynamics routinely undermine well-intentioned policy, not because of bad faith or poor evidence, but because the analytic frameworks used to design and evaluate policy fail to account for real-world behavior. The Adaptive Policy Coherence Framework (APCF) is a governance-grade analytic framework developed to address this gap. Rather than predicting outcomes or prescribing decisions, APCF provides a structured, transparent method for examining how policy assumptions interact with adaptive behavior across stakeholders, institutions, and markets. Its purpose is to improve policy coherence, robustness, and defensibility by explicitly surfacing where intended mechanisms diverge from observed or plausible real-world responses. APCF integrates insights from complex systems science, institutional economics, and behavioral dynamics with a strong emphasis on interpretability and auditability. Drawing on established scientific foundations—such as renormalization and coarse-graining in physics, decoherence and selection under interaction, and empirical work on institutional adaptation—the framework treats policy environments as systems subject to pressure, substitution, and constraint. Within this view, policy success depends not on ideal compliance but on whether its core assumptions remain coherent under realistic conditions. Crucially, APCF is human-led and non-automated. It is not an artificial intelligence system, a predictive model, or an enforcement tool. It does not target individuals, optimize behavior, or generate prescriptions. Instead, it functions as an analytic scaffold that supports structured reasoning, interdisciplinary synthesis, and governance-ready documentation. All assumptions, uncertainties, and trade-offs remain explicit and reviewable. The framework is designed to be adaptable across domains and jurisdictions, making it suitable for applications in public health, regulatory design, environmental governance, supply-chain oversight, and other policy contexts characterized by adaptive response and institutional complexity. This preprint presents the conceptual foundations of APCF, its analytic structure, and its intended use as a decision-support tool for policymakers, regulators, and institutional stakeholders seeking to design policies that remain coherent under real-world pressure.