University AI policies score higher on delegation boundaries than on evidence standards¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change

Subclaims¶

q2 i? In the 30-institution audit, mean delegation-boundary score was 2.47/4 versus mean evidence-standard score of 1.89/4, with 22 policies scoring higher on boundary than evidence. → Kai Yao 2026

Evidence¶

Kai Yao 2026¶

Kai Yao. (2026). What Does the Credential Still Certify? Cognitive Stewardship for AI-Mediated Education. arXiv preprint. https://arxiv.org/abs/2607.19988 doi:10.48550/arxiv.2607.19988

q2 · i? · associational · r1

Policy audit of public generative AI assessment guidance from 30 universities across five national systems, scored by four open-weight LLM coders under a pre-specified codebook. It found "22 policies scored higher on boundary than evidence, 3 tied, and only 5 reversed the gap."

"24 reached a delegation-boundary score of at least 2, and the mean boundary score was 2.47/4. The weaker element was the evidence standard. Its mean was 1.89/4; 22 policies scored higher on boundary than evidence, 3 tied, and only 5 reversed the gap."

Discussion¶

Related Claims¶

• Policy packages fall into four archetypes defined by which design element is missing — related
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• Judgement-bearing assistance is the central analytic pivot: delegating evaluation of quality and correctness is normatively more demanding than instrumental assistance — related
• Output-verification support is the least covered scenario in policy guidance — related