urn:uuid:d016383a-3cee-5173-b17f-e8685651d2dc New versions of this research opportunity and changes to the claims it rests on. 2026-10-21T00:00:00Z SocioLens urn:uuid:a722cf9b-de44-5a9b-a994-4b1e80bf0107 2026-10-21T00:00:00Z

What changed: The corrected disparity figures are no longer held back. The main result now gives them from the authors’ corrected analysis: for discretionary referrals in 2016–18, the gap between the screen-in rates of Black and white children was 17.9 percentage points for AFST-only (counterfactual) decisions (67.9% against 50.0%) and 7.1 points for decisions by workers using the AFST (50.2% against 43.1%). The public-facing claim now leads with the disparity result that the correction supports, and gives the 21.0% override share second, as a figure of the original analysis whose numbers the authors later said all changed. The limitations add that the corrected analysis is a preprint, that its authors did not report the override share again, and that the study period and population of the 21.0% share are not recorded here. The direction of the claim, its sources, scope and verification state are unchanged. Why: Version 1.0 held back the exact 17.9→7.1 figure (marked HOLD in the R04 LD-05 Canonical Claim Ledger v1.0), pending direct extraction from the corrected analysis. On 21 October 2026 the full text of Stapleton et al., arXiv:2204.13872v1 (29 April 2022), was read line by line. Appendix A, "Detailed Comparisons of Analyses 1 and 2", first point, Analysis 2 column, reports that AFST-only decisions would have screened in 67.9% of Black and 50.0% of white children in discretionary referrals from 2016-18, "a racial disparity of 17.9%", and that workers using the AFST screened in 50.2% and 43.1%, "a disparity of 7.1%". The paper’s own "%" is a difference between two rates, so this version calls it percentage points. The check read a text extraction of the PDF and looked at its figure pages. The paper’s Figure 1(b) plots the same screen-in rates; it labels the AFST-only gap 17.9% but the worker+AFST gap 7.0%, 0.1 point below the 7.1% of Appendix A. This version follows the appendix text and its rates, whose difference is 7.1 points. Section 2 of the same paper says that "all of the specific numbers we reported in Analysis 1 changed in Analysis 2"; the HQ batch notes take the 21.0% override share from the original CHI 2022 paper, which reports Analysis 1, and the corrected analysis does not report that share again. The CHI 2022 paper itself was not read for this revision (the ACM Digital Library blocks the project’s tools), so the attribution of the 21.0% share to the original analysis rests on the HQ batch notes. The check and this revision were done by AI agents reading the paper, not by a person.

urn:uuid:adb2cab7-edfe-51ee-9c1c-6d159da8058b 2026-10-13T00:00:00Z

Narrowed after the literature check. The claim that no cross-system compilation of override rates exists is too broad. In offender risk assessment there is an established override literature that reports override rates and direction across tools and jurisdictions, now synthesised in a 2025 scoping review and meta-analyses of 21 studies covering eight tools (Psychology, Public Policy, and Law 31(3), doi:10.1037/law0000448), and single studies there report rates from about 7% to 74% with upward and downward overrides coded separately. No compilation was found for benefits, employment services, child welfare, pretrial or immigration systems, or across those sectors under one definition, so the opportunity should be narrowed to those sectors and use the correctional literature as a benchmark and coding template. The verdict changed from "No study found doing the core design" to "Related work exists".

urn:uuid:941c983e-f44f-5930-bd00-a6127f3c596e 2026-10-12T00:00:00Z

Across deployed public-sector risk and profiling systems, how often do officials formally or informally depart from the system's recommendation, in which direction, and how much of the variation between systems survives once override is defined and counted the same way?