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SRC-fe2580c52f140ba4 · Source record

Synthetic Replacements for Human Survey Data? The Perils of Large Language Models

Political Analysis / authors · 4 connected claims

D01 · Marketing, Brand & Revenue SystemsD03 · Intelligence, Research & Decision ProductsD11 · AI Models, Agents & Human–AI InteractionD19 · Measurement, Experimentation & EconomicsD20 · Consumer, Culture & Lifestyle FuturesD22 · Policy, Geopolitics & Societal Change

Canonical route

https://www.cambridge.org/core/journals/political-analysis/article/synthetic-replacements-for-human-survey-data-the-perils-of-large-language-models/B92267DC26195C7F36E63EA04A47D2FE

Claims connected to this source

  1. MWITA-SR-2026-003ChatGPT synthetic feeling-thermometer means were close to ANES means while response dispersion was lower than in the human surveys.Evidence A
  2. MWITA-SR-2026-004Regression coefficients from synthetic responses often differed significantly from estimates using the human ANES sample.Evidence A
  3. MWITA-SR-2026-005The benchmark found exaggerated ideological out-group antipathy in some persona-conditioned outputs.Evidence A
  4. MWITA-SR-2026-075No source in this bundle demonstrates an independently audited commercial decision outcome caused by synthetic-consumer evidence.Evidence D

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