Electoral Incentives in Mixed-Member Systems: Party, Posts, and Zombie Politicians in Japan
Bibliographic record
Abstract
How do electoral incentives affect legislative organization? Through an analysis of Japan's mixed-member electoral system, we demonstrate that legislative organization is strongly influenced not only by the individual legislators reelection incentives but also by their interest in their party gaining power and maintaining a strong party label. Electorally vulnerable legislators are given choice legislative positions to enhance their prospects at the polls, whereas (potential) party leaders disproportionately receive posts with greater influence on the party's overall reputation. Members of Parliament elected from proportional representation (PR) lists and in single member districts also receive different types of posts, reflecting their distinct electoral incentives. Even small variations in electoral rules can have important consequences for legislative organization. In contrast to Germany's compensatory mixed-member system, Japan's parallel system (combined with a “best loser” or “zombie” provision) generates incentives for the party to allocate posts relating to the distribution of particularistic goods to those elected in PR.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".