Bibliographic record
Abstract
It is often taken for granted that parties support electoral reform because they anticipate seat payoffs from the psychological and mechanical effects of the new electoral system. Although some studies point out that elements related to values and the willingness to achieve social goals are also relevant to explaining party preference in those situations, a general model of how these considerations influence support for electoral reform is still missing. To fill this gap, I develop in this article a policy-seeking model accounting for values-related factors and operationalize it using one of the most firmly established effects of electoral systems in the literature: The degree of inclusiveness and its consequences for the representation of social groups in parliament. The empirical relevance of this model is then tested using an original dataset reporting the actual position of 115 parties facing 22 electoral reform proposals in OECD countries since 1961. The results show that willingness to favour the electoral system most in line with a party’s electoral platform has a unique explanatory power over party support for a more proportional electoral system. In turn, values appear to be as crucial as party self-interest in explaining the overall electoral reform story.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".