Remaking Government in Canada: Dares, Resilience, and Civility in Westminster Systems
Bibliographic record
Abstract
By 2015 concern had emerged about the trajectory of Canada's Westminster model and the state of democratic governance under successive Harper governments, particularly with respect to transparency and relationships with public servants, which among other things led to the election of the Trudeau government in October 2015. This article compares these developments with the wholesale reform experiences in Australia, New Zealand, and the United Kingdom. We consider not only the evolving bargains between prime ministers and their ministers, political advisors, top officials, and legislatures, but also between party leaders and political parties, and between governments and civil society. Second, we characterize far‐reaching reforms as “dares,” intended to change the trajectory of Westminster systems, which carry political risks. Third, we consider the resilience of Westminster systems in the face of significant change and inaction. The Harper reforms were not nearly as dramatic as those of the United Kingdom, New Zealand, and Australia during the late 1980s but did change the bargain with civil society, foundational to Westminster systems. The essential principles of responsible government have stood up well to the test of experience, and will serve as well tomorrow as they have in the past. However, parliamentary government is an inherently evolutionary form of government. Task Force on Public Service Values and Ethics ( , 17)
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.041 | 0.025 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".