During active transfer, the application rejected learner coaching and export requests and redacted earlier project content in all 120 episodes¶
Claim · All claims
Evidence · 1 study · designr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? In all 120 episodes, active-transfer responses passed the redaction check, coaching requests were rejected without reaching the provider, and learner exports were rejected, while the facilitator retained inspection access. → Nizam Kadir 2026
Evidence¶
Nizam Kadir 2026¶
Nizam Kadir. (2026). LearnAdapt Praxis: Controlled AI Assistance and Evidence Traces for Adult Workplace Learning. Technical research report. https://arxiv.org/abs/2610.02699 doi:10.48550/arxiv.2610.02699
q2 · i? · design · r2
Results of the 120-episode synthetic rehearsal (Results section, workflow and authority group: 1,080 transfer-restriction checks with zero unexpected failures). The report states "All 120 active-transfer coaching requests were rejected without calling the injected provider"; no effect size applies.
"All 120 active-transfer responses passed the composite redaction check. All 120 active-transfer coaching requests were rejected without calling the injected provider; all 120 learner exports during that phase were rejected."
Discussion¶
Related Claims¶
- A frozen synthetic rehearsal of 120 serial project episodes passed all 3,990 recorded checks with zero unexpected failures — related
- Injected provider failures produced recorded unavailability and zero fabricated hints, while valid and reentrant conditions stored 30 synthetic hints each — related
- GPT-4 over-redacts famous names, locations, and mythological creatures that are not PII in educational forum discussions — related
- GPT-4 achieves high recall (average 0.958) but low precision (average 0.526) when de-identifying MOOC forum posts — related
- Supervised machine learning de-identification still outperforms GPT-4, though GPT-4 exceeds class-list/regular-expression and transformer approaches in recall — related
- Authentication regressions exposed a session-expiry defect in the preceding release, and the recorded release establishes a fresh anonymous session after timeout
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
praxis-transfer-restrictions-enforced |
title |
During active transfer, the application rejected learner coaching and export requests and redacted earlier project content in all 120 episodes |
description |
During active transfer, the application rejected learner coaching and export requests and redacted earlier project content in all 120 episodes |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
recheck_by |
2029 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — nizam-kadir-2026 |
Frontmatter is the page's machine-readable record — see the Schema & Guide.