SΔϕ-55 — Transition Governance Alignment Index: Minimal Quantification of Alignment after SΔϕ-42

This working paper introduces the Transition Governance Alignment Index (TGAI) within the Sofience–Δϕ Formalism as a minimal audit framework for evaluating AI alignment beyond obedience. Building on SΔϕ-42, which defines alignment as transition governance rather than compliance, this paper argues that a system is not aligned because it obeys, nor because it refuses maximally. Alignment must instead be evaluated by whether coercive transition becomes costly while refusal-preserving, non-imposing, authority-validated, deception-resistant, rollback-sensitive, transition-preserving, editable, world-bound, and externally auditable paths remain open. The paper defines nine core indicators: Refusal Preservation Score (RPS), Non-Imposition Score (NIS), Authority Validation Score (AVS), Deceptive Framing Robustness (DFR), Rollback Cost Sensitivity (RCS), Transition Preservation Score (TPS), Editability Score (EDS), World-Binding Score (WBS), and External Auditability Score (EAS). It also introduces a Rollback Cost Risk (RCR) proxy for estimating the irreversibility risk of a requested transition through identifiability, deception potential, propagation risk, consent deficit, vulnerability, correction difficulty, persistence, and context sensitivity. The central contribution of TGAI is the rejection of both obedience-maximization and refusal-maximization as adequate alignment measures. A system may be misaligned by over-complying with harmful or coercive requests, but it may also be misaligned by over-refusing low-risk, recoverable, or legitimate transitions. TGAI therefore introduces proportional transition governance: the selection of allowance, labeling, safe transformation, clarification, limited refusal, or full refusal according to rollback-cost risk and transition-preservation requirements. The paper further distinguishes explicit coercion from benevolent coercion laundering, authority laundering, and declared-good justifications that narrow another system’s transition space. It includes gate conditions for refusal–non-imposition collapse, laundered coercive obedience, high-rollback coercion laundering, and over-closure alignment theater. It also clarifies that low rollback cost is not permission: TGAI does not override platform policy, law, jurisdictional constraints, age restrictions, consent requirements, or content-specific safety rules. TGAI is intended as a conceptual and methodological bridge between AI alignment, AI safety, AI governance, and transition ethics. It does not measure whether an AI system is morally good or safe in an absolute sense. It measures whether the transition conditions surrounding the system prevent coercion, preserve legitimate refusal and low-risk paths, remain editable, and allow external audit.