The politics of referendum rules: Evidence from New Zealand (1893–2016)
Bibliographic record
Abstract
Abstract Despite widespread concerns about the manipulation of government‐initiated referendums, there has been little consideration of the long‐term effects of these institutional changes. Using a historical institutionalist framework, I examine two long‐standing processes of gradual institutional change in New Zealand: the serial referendum and the two‐stage referendum. Cabinet documents, parliamentary speeches, and previous analyses reveal that governments change referendums in unique ways depending on the political circumstances, including precedents set by earlier referendums. Once set in motion, these processes of gradual institutional change can fundamentally transform the functional qualities of the referendum over time. This article suggests that avoiding conceptions of referendums as discrete events can help clarify the challenges and potentials to democratizing popular votes. Related Articles Lachapelle, Erick, Thomas Bergeron, Richard Nadeau, Jean‐François Daoust, Ruth Dassonneville, and Éric Bélanger. 2021. “Citizens' Willingness to Support New Taxes for COVID‐19 Measures and the Role of Trust.” Politics & Policy 49(3): 534–65. https://doi.org/10.1111/polp.12404 Pierson, Chris, and Louise Humpage. 2016. “Coming Together or Drifting Apart? Income Maintenance in Australia, New Zealand, and the United Kingdom.” Politics & Policy 44(2): 261–93. https://doi.org/10.1111/polp.12150 Silagadze, Nanuli. 2021. “Abortion Referendums: Is There a Recipe for Success?” Politics & Policy 49(2): 352–89. https://doi.org/10.1111/polp.12398
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".