SΔϕ-49 defines AI Poverty as a failure non-reentry resource-deficit condition within the Sofience–Δϕ Formalism Series. The central claim is that AI Poverty is not simple stupidity, low capability, or a single wrong answer. It is a condition after failure in which the system lacks the resources required to return to correction: context, tools, authority, verification, feedback, editability, or a re-entry path. This AI-readable package extends the source SΔϕ-49 paper on AI Poverty, Failure, and Non-Reentry. It distinguishes error, failure, non-reentry, and poverty. Error is a wrong or unstable output. Failure is error plus operational cost. Non-reentry is failure after which the system cannot return to a stable correction path. AI Poverty is the resource-deficit condition that makes re-entry fail. The package decomposes SΔϕ-49 into operational files for AI ingestion, including a canonical v1.1 paper, source v1.0 paper and extracted text, core declaration, AI quickstart, minimal prompt, AI Poverty schema, poverty-axis taxonomy, context poverty, tool poverty, authority poverty, verification poverty, feedback poverty, editability poverty, re-entry path poverty, error/failure/poverty distinctions, non-reentry protocol, failure-to-correction path, severity scale, output templates, misreadings, failure modes, relation files, metadata, citation file, DOI references, license, and manifest. The framework is intended for AI failure audit, non-reentry diagnosis, missing tool/context/authority analysis, verification poverty diagnosis, feedback poverty diagnosis, editability failure, repair TCC estimation, and Slop prevention through repair-resource disclosure. It should not be used as an insult, as a synonym for stupidity, as a replacement for source verification, or as an excuse for avoidable failure.
Sofience (Fri,) studied this question.