Do politicians anticipate voter control? A comparative study of representatives’ accountability beliefs
Bibliographic record
Abstract
Abstract Representation literature is rife with the assumption that politicians are responsive to voter preferences because their re‐election is contingent upon the approval of those voters, approval that can be won by furthering their desires or, similarly, that can be threatened by ignoring their wishes. Hence, scholars argue that the anticipation of electoral accountability by politicians constitutes a crucial guarantor of (policy) responsiveness; as long as politicians believe that voters are aware of what they do and will take it into account on election day, they are expected to work hard at keeping these voters satisfied. If, on the other hand, politicians were to think what they say and do is inconsequential for citizens’ voting behaviour, they may see leeway to ignore their preferences. In this study, we therefore examine whether politicians anticipate electoral accountability in the first place. In particular, we ask 782 Members of Parliament in Belgium, Germany, Canada and Switzerland in a face‐to‐face survey about the anticipation of voter control; whether they believe that voters are aware of their behaviour in parliament and their personal policy positions, are able to evaluate the outcomes of their political work, and, finally, whether this knowledge affects their vote choice. We find that a sizable number of MPs believe that voters are aware of what they do and say and take that into account at the ballot box. Still, this general image of rather strong anticipation of voter control hides considerable variation; politicians in party‐centred systems (in Belgium and some politicians in Germany that are elected on closed party lists), anticipate less voter control compared to politicians in more candidate‐centred systems (Canada and Switzerland). Within these countries, we find that populist politicians are more convinced that voters know about their political actions and take this knowledge into account in elections; it seems that politicians who take pride in being close to voters (and their preferences), also feel more monitored by these voters. Finally, we show that politicians’ views of voter control do not reflect the likelihood that they might be held to account; politicians whose behaviour is more visible and whose policy profile should therefore be better known to voters do not feel the weight of voter control more strongly.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".