Beyond the Name: Demographic Leakage in De-Identified Résumés and Evaluation Artifacts in LLM Bias Audits

• URL: http://arxiv.org/abs/2609.16501v1
• Date: Tue, 15 Sep 2026 01:48:44 GMT
• Title: Beyond the Name: Demographic Leakage in De-Identified Résumés and Evaluation Artifacts in LLM Bias Audits
• Abstract summary: We investigate whether eliminating language fields resolves leakage across nine open-weight models and 620 résumés.<n>We isolate unstructured prose across five ethnocultural conditions and three cue-salience tiers.<n>Target-group recovery averages 0.757 overall and saturates at 1.000 under high salience.
• Score: 4.736836688901646
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: De-identified résumé screening assumes that redacting explicit fields prevents ethnocultural inference; however, recent audits attribute residual leakage to declared languages. We investigate whether eliminating language fields resolves this leakage across nine open-weight models and 620 counterfactual résumés. By holding language attributes strictly identical, we isolate unstructured prose across five ethnocultural conditions and three cue-salience tiers. Target-group recovery averages 0.757 overall and saturates at 1.000 under high salience, demonstrating that non-language prose sustains demographic inference. Crucially, models diverge only under faint cues (0.086-0.690), establishing salience as an essential evaluation axis. Furthermore, pairwise LLM-as-a-judge outcomes are highly sensitive to evaluation design: forbidding ties yields an apparent selection-rate ratio of 0.39 alongside strong position and content effects, whereas permitting ties produces near-universal ties for most models ($\ge94\%$). Downstream scoring shows only very small between-condition differences, highlighting the need to distinguish demographic signals recoverable from résumé content from effects introduced by the evaluation protocol.

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