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News/Two Wrongs, No Right: Auditing Social-Desirability Bias in LLM Annotators for Computational Social Science
arxiv
PublishedJune 12, 2026 at 4:00 AM
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Two Wrongs, No Right: Auditing Social-Desirability Bias in LLM Annotators for Computational Social Science

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Publisher summary· verbatim

arXiv:2606.12426v1 Announce Type: cross Abstract: LLM annotators are increasingly used in computational social science (CSS), but it is unclear whether their alignment-shaped errors preserve the empirical conclusions a researcher would report. We audit three open-source 7B instruction-tuned models (

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    Zephyr
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#bias#computational social science#language models#validation

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Mentioned models
03
  • 01
    Zephyr
  • 02
    Mistral
  • 03
    Qwen
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#bias#computational social science#language models#validation

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