The Effects of Proportional Representation on Election Lawmaking: Evidence from New Zealand
Bibliographic record
Abstract
It is widely recognised that politicians are self-interested and desire election rules beneficial to their re-election. Although partisanship in electoral system reform is well-understood, the factors that affect partisan manipulation of other democratic ‘rules of the game’ – including election administration, franchise laws, and campaign finance – has received little attention to date. New Zealand is so far the only established democracy to shift from a non-proportional to a proportional electoral system and thus presents an ideal case to test the effects of electoral system change on the politics of election reform. This article examines partisan and demobilising election reforms passed between 1970 and 1993 under first-past-the-post and between 1997 and 2020 under mixed-member proportional representation. Moving to a proportional system has failed to diminish the amount of partisan election lawmaking, though voting restrictions have become less common. These results should caution against claims that reforming a country’s electoral system will necessarily curtail the passage of normatively undesirable election reforms.
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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 | 0.011 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".