Knowledge Resource
Research Summary: Reproducibility is not construct validity: LLM measurement of institutionally situated communication
- Original authors
- Attribution requires verification
- Original source
- arXiv — Computers and Society
- Summary & Analysis prepared by
- Aziz Shuaib Ausi
- Resource type
- Research Summary / Knowledge Resource
- Resource published on AZIZ OS
- 18 September 2026
- Reading time
- 1 min
- Publication type
- Knowledge Resource
- Availability
- Open access
About this Summary & Analysis
AZIZ OS provides independently prepared summaries and analytical interpretations of externally published research and knowledge sources. The underlying works remain attributable to their original authors and rights holders. This resource is intended to improve accessibility and understanding and does not replace the original publication.
Recent research indicates that while Large Language Model (LLM) annotations of qualitative data can achieve high levels of reproducibility, this does not guarantee their construct validity. An analysis of the European Commission's AI Act consultation data demonstrated that LLM-inferred measures, despite high reproducibility, showed limited convergence with survey-reported measures intended to capture the same construct, particularly varying across different stakeholder groups.
Why it matters
This finding highlights a critical distinction between consistency of measurement (reproducibility) and accuracy of measurement (construct validity) when employing advanced AI tools like LLMs for data analysis. Misinterpreting LLM outputs can lead to flawed insights, impacting strategic decision-making and policy formulation across various domains.
Key insights
- LLM annotations of text-based data exhibited high reproducibility, with intraclass correlations exceeding 0.99, suggesting consistency in measurement.
- Despite high reproducibility, LLM-inferred measures demonstrated limited convergence with independently collected survey-reported measures of the same nominal construct.
- The divergence between LLM-inferred and survey-reported text-based measures varied systematically across different stakeholder groups.
- Business associations, for example, expressed greater concern about AI risks in their text-based consultation submissions compared to their survey responses, according to the LLM analysis.
Source
arXiv — Computers and Society — https://arxiv.org/abs/2609.19866
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- Verification ID
- ASA-EXE-2026-00737
- Version
- v1.0 · r0
- Issued
- 18 September 2026
- Resource prepared by
- Aziz Shuaib Ausi
- Resource status
- Research Summary / Knowledge Resource
- Underlying work
- Reproducibility is not construct validity: LLM measurement of institutionally situated communication
- Original authors
- Attribution requires verification
- Original source
- arXiv — Computers and Society
- Provenance status
- Attribution requires verification
- Rights
- Underlying publication rights remain with the respective copyright holder(s). Refer to the original source for authoritative publication and licensing information.
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