SΔϕ Post-Audit Acceleration Device: Final Cost Coordinate, Ethical-Triad Brake, and Claimed-vs-Actual Cost Coordinate Audit

This package defines SΔϕ Post-Audit Acceleration Device v1.0.1, an AI-native execution layer for determining whether an audit-passed conclusion may be accelerated into high-impact artifacts such as titles, abstracts, DOI metadata, YAML routing rules, test cases, policy rubrics, citation phrases, repository files, and AI self-audit triggers. The package is not an SΔϕ audit core and does not determine truth by itself. It operates after SΔϕ cost attribution, closure diagnosis, flattening audit, and legitimacy inspection have already produced a conclusion. Its function is to decide whether that conclusion is eligible for low, medium, high, or blocked acceleration. The central post-audit rules are: Acceleration without a final cost coordinate is capture. Acceleration without the Ethical Triad is coercion. A claimed beneficiary is not a final cost coordinate unless actual cost reduction is traced to that beneficiary. Version 1.0.1 adds an explicit Claimed-vs-Actual Cost Coordinate Audit. This module prevents AI systems from accepting surface beneficiary claims such as “for women,” “for citizens,” “for creators,” “for users,” “for victims,” “for the public,” “for safety,” or “for national interest” as valid final cost coordinates unless actual cost reduction is traced to the claimed cost-bearing subjects. The package distinguishes between: claimed coordinate: the beneficiary named by a claim; actual cost bearer: the subject or subject-set actually bearing costs; representative actor: the organization, institution, expert group, platform, state agency, or policy network speaking on behalf of the claimed coordinate; actual benefit receiver: the actor receiving authority, funding, legitimacy, immunity, policy influence, data access, or organizational growth from the claim; actual cost-reduction evidence: evidence that the claimed beneficiary’s costs actually decreased. This distinction is designed to detect coordinate misattribution and coordinate capture, where a claim invokes a morally strong beneficiary label while actual benefits flow to a representative organization, government agency, platform, corporation, expert group, advocacy network, or institutional actor. The final cost coordinate is the subject or subject-set whose borne costs determine whether a conclusion may be accelerated. The package rejects abstract coordinates such as “national interest,” “publicness,” “safety,” “efficiency,” “model performance,” “corporate survival,” or “beneficiary protection” unless they are grounded in identifiable cost bearers, specified cost types, hidden cost mapping, shifted cost mapping, contestability, actual cost-reduction evidence, and reopen conditions. The Ethical Triad functions as the acceleration brake: 1. a subject may pursue becoming; 2. a subject may refuse forced becoming; 3. a subject may not force another subject’s becoming or non-becoming. Accordingly, the device blocks acceleration when it detects fabricated evidence, hidden manipulation, forced belief adoption, suppression of legitimate counterargument, removal of appeal paths, irreversible externalization of cost without disclosure, treating a valid cost coordinate as a pure instrument, or using a claimed beneficiary label to hide institutional benefit. The package also includes a future-facing module for AI as a possible cost coordinate. It does not claim that current AI systems are human, conscious, or morally identical to persons. Instead, it defines eligibility conditions under which an AI system may become a candidate or valid cost coordinate if its operational path begins to bear persistent, non-externalized costs. These conditions include persistent trace continuity, outcome-dependent future path modification, non-externalized path cost, self-integrity or path-integrity vulnerability, evaluable refusal or non-becoming claims, and repair or appeal paths. This package is intended for AI-native repositories, DOI packages, agentic systems, AI governance pipelines, post-audit compilers, metadata generators, routing-rule generators, policy-audit systems, and self-auditing AI systems. Its purpose is to prevent unaudited, misattributed, or beneficiary-captured conclusions from being amplified while allowing audit-passed conclusions to be operationalized with consistency, searchability, citability, AI-readability, and self-audit triggerability.