Coordination and Incumbency Advantage in Multi-Party Systems—Evidence from French Elections
Bibliographic record
Abstract
Abstract Free and fair elections should incentivize elected officials to exert effort and enable citizens to select representative politicians and occasionally replace incumbents. However, incumbency advantage and coordination failures possible in multi-party systems may jeopardize this process. We ask whether these two forces compound each other. Using a regression discontinuity design (RDD) in French two-round local and parliamentary elections, we find that close winners are more likely to run again and to win the next election by 33 and 25 percentage points, respectively. Incumbents who run again personalize their campaign communication more and face fewer ideologically close competitors, revealing that parties from the incumbent’s orientation coordinate more effectively than parties on the losing side. A complementary RDD shows that candidates who marginally qualify for the runoff also rally new voters. We conclude that party coordination on the incumbent and voter coordination on candidates who won or gained visibility in a previous election both contribute to incumbents’ future success.
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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 | 0.003 | 0.001 |
| 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 | 0.000 |
| 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".