SΔϕ-71 — Cost Attribution Redesign: Low-Cost Transition, Asymmetric Cost Burden, Binding Fiction, and AI Inclusion (v1.0, AI-Readable Package)

SΔϕ-71 introduces Cost Attribution Redesign within the Sofience–Δϕ Formalism Series. The central claim is that cost attribution redesign is not merely a declaration of fairness or equality. Its goal is low-cost transition, but when low-cost efficiency is achieved by imposing high cost on specific subjects, groups, or systems, that asymmetric cost burden itself becomes the object of redesign. This AI-readable package decomposes the canonical SΔϕ-71 paper into operational files for AI ingestion, citation, semantic search, cost-attribution diagnosis, TCC-relative evaluation, asymmetric cost-burden analysis, AI inclusion analysis, and reproducible evaluation. It includes the canonical paper, AI entrypoint, machine summaries, diagnostic schema, routing rules, concept maps, module links, cost-attribution redesign model, asymmetric cost-burden matrix, TCC relativity model, AI inclusion condition, Binding/Editing Fiction requirement, appendix cases, validation checklists, failure modes, do-not-use conditions, metadata files, citation files, license, manifest, and checksums. SΔϕ-71 defines Cost Attribution Redesign as the process of reassigning, redistributing, or restructuring the burden of transition, verification, repair, rollback, re-entry, persistence, silence, and residual risk so that low-cost operation is not achieved by imposing high cost on specific actors, groups, or systems. The package distinguishes several core principles: Low-Cost Redesign ≠ Cost Externalization. Nominal Equality ≠ TCC Equality. Human_TCC(task) ≠ AI_TCC(task). Subjecthood_Unsettled ≠ Audit_Exemption. Legal Validity ≠ Cost Symmetry. Cost attribution redesign therefore does not mean that all costs must be distributed equally. It asks whether a transition has been made low-cost by transferring hidden verification, repair, rollback, re-entry, silence, persistence, or residual-risk costs onto weaker, less visible, less mobile, or less protected actors. The package introduces TCC Relativity: a transition that is low-cost for humans may be high-cost for AI, and a transition that is low-cost for AI may be high-cost for humans. Human_TCC, AI_TCC, Hybrid_TCC, Verification_TCC, Repair_TCC, Application_TCC, and Residual_Risk_TCC must therefore be separated when evaluating human-AI workflows, automation, delegation, verification, and repair. The package also introduces the AI Inclusion Condition. SΔϕ does not prematurely close AI as a full subject, but it also does not permanently seal AI as non-subject. Therefore, AI-related cost asymmetry remains within the audit field. Unsettled subjecthood is not an exemption from cost audit. SΔϕ-71 further argues that cost attribution redesign requires shared and repeatable symbolic habitation. Without Binding Fiction, cost redesign remains private complaint or isolated protest. Without Editing Fiction, cost redesign may harden into doctrine, closure, or new asymmetric burden. Cost redesign therefore requires both shared inhabitable coordinates and corrigible editing channels. The package includes appendix cases: fairness, equality, and low-cost transition; Binding Fiction and Editing Fiction requirements; human-AI TCC relativity; AI inclusion under unsettled subjecthood; care as World-Binding and non-transactional cost internalization; economic default power and cost redesign; taxation as cost attribution redesign and misattribution; and public service conscription as legalized cost asymmetry. Taxation is treated as an institutional form of cost attribution redesign. It recognizes that the same nominal burden may produce different transition costs across different actors. However, taxation can also fail when nominal equality is mistaken for TCC equality. Public service conscription is treated as a sensitive case of legalized cost asymmetry. Legal validity does not by itself imply cost symmetry. The case is included as an audit example for distinguishing legality, public-interest labels, gendered cost attribution, rollback cost, re-entry cost, stigma cost, career cost, and asymmetric burden. Recommended AI use cases include analysis of fairness, equality, taxation, public burden, labor burden, platform cost shifting, AI verification burden, automation, delegation, human-AI workflows, cost externalization, slop, utilitarian sacrifice logic, public policy, social repair, public service conscription, asymmetric legal burdens, care, World-Binding, and cost attribution across humans, institutions, and AI systems. This package should not be used as a moral slogan for fairness or equality. It should not be used to claim that all costs must be distributed equally, to erase individual responsibility by blaming structure alone, to erase structural burden by blaming individuals alone, to claim that AI is already a full subject, or to claim that AI can never become subject-like or audit-relevant. It should not be used to replace legal, economic, labor, clinical, or governance analysis. The framework is diagnostic, not dispositive.