Reproducibility data and code for Human Review Is Not Recourse: Auditing Challenge and Remedy in Operational AI-Assisted University Admissions

Reproducibility data and Python code for the documentary audit reported in Human Review Is Not Recourse: Auditing Challenge and Remedy in Operational AI-Assisted University Admissions. The dataset covers 33 operational admissions pathways in five countries (28 in the United States) and records explicit, partial or indirect, and not-publicly-documented states across eight propositions. The package regenerates categorical counts, downstream profiles, stratified summaries, the record-linked sensitivity analysis, and figures. It includes dated source, population, search, and coding-change ledgers. The historical two-pass summaries are not a complete candidate or screening register. Recalculation checks numerical consistency and does not independently validate source judgments or practical recourse effectiveness. Raw correspondence, correspondence summaries, non-public student-level data, manuscript files, and internal QA are excluded. Component-specific licenses apply: original Python code is licensed under MIT; original data, coding judgments, compilations, and documentation are licensed under CC BY 4.0. These are not alternative licenses for the whole package. Attributed third-party excerpts and materials are excluded from the author-granted licenses and remain subject to their original rights. See RIGHTS_NOTICE.md and the license files for scope. This deposit does not imply journal acceptance.