The Credibility of Party Policy Rhetoric Survey Experimental Evidence
Why this work is in the frame
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Bibliographic record
Abstract
This article analyzes how a party’s policy statements affect voters’ perceptions of where the party stands on a given issue. I argue that voters do not take a party’s statements at face value because these messages can be a strategic tool to win elections. Voters discount popular statements because they may respond to vote-seeking incentives rather than reflect the party’s sincere views. Espousing unpopular policies has less instrumental value in obtaining more votes and therefore is more credible. I have tested this argument with a survey experiment fielded in the United Kingdom that exposes respondents to Conservative and Labour Party statements on immigration and the National Health Service. I report evidence that popular statements tend to have a weaker effect on voter perceptions than unpopular ones. This finding suggests a paradox: the more a party needs to change its reputation in order to gain votes, the stronger the voters’ skepticism.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it