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arXiv:2608.27309cs.CL

Difference-in-Differences on a Censored Rating Scale Can Manufacture an Effect: Evidence from a Pre-Registered LLM-Judge Audit

Shuyi Fan, Boyuan Deng, Mengyu Xu, Xinhong Xie, Chenyang Li, Hongyang Zhang

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Abstract

LLM-judge audits assess bias by comparing ratings across matched conditions. Difference-in-differences designs take the rating difference between two candidate responses to each item and compare it across a manipulated attribute. Building on prior work on nonlinear difference-in-differences, we show in closed form that when ratings are bounded, a severity shift common to both responses produces an observed interaction whenever the scale bounds attenuate it unequally. We then report a pre-registered audit of 990 calls to a frozen pedagogy judge. The registered primary analysis did not detect an effect of a stated novice or advanced profile on scaffolding preference. The only nominally significant secondary interaction was on the productive-struggle sub-score ($+0.378$ points; $p = 0.002$). A post-hoc construction with zero differential preference reproduced 79 to 85% of this interaction using the observed severity shift and the scale floor alone. The observed interaction therefore does not identify differential preference on the latent scale.

arXiv comments
Accepted at NewInML Workshop at NeurIPS 2026. Code available at https://github.com/bydeng01/ability-levels-audit
Journal reference
DOI
Subjects
cs.CLComputation and Language cs.AIArtificial Intelligence cs.CYComputers and Society

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