The role of politicians' perceptual accuracy of voter opinions in their reelection
Bibliographic record
Abstract
Abstract Political representation can be described as a process brought about via an electoral and a perceptual path. Drawing on original survey data on the perceptual accuracy of elected representatives in Belgium, Canada and Switzerland, this study explores whether and how the two paths are connected. It shows, first, that representatives who more accurately perceive voters' opinion are more likely to be re‐elected, suggesting that perceptual accuracy impacts the electoral path to representation. Second, representatives who are electorally safe hold less accurate perceptions of voters' policy preferences, meaning that the electoral path impacts the perceptual path. In all, the study provides evidence for the role of politicians' perceptual accuracy in their electoral career: voters sanction those representatives who are not sufficiently acquainted with their preferences, and representatives who fear to be voted out of office put more effort in getting acquainted with what voters want.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".