Municipal reform in Canada : reconfiguration, re-empowerment and rebalancing
Bibliographic record
Abstract
Preface Part I: Introduction 1. Overview: Reconfiguration or Reinvention of Municipal Government? Part II: Municipal Reform in the Provinces and Territories: Case Studies 2. Local Government Reform in British Columbia, 1991-2005: One Oar in the Water 3. Muncipal Reform in Alberta: Breaking Ground at the New Millennium 4. Saskatchewan's Municipal Reform Agenda: Plethora of Processes and Proposals but Paucity of Products 5. Municipal Reform in Manitoba 6. Municipal Reform in Ontario 7. Municipal Reform in Quebec: The Trade-off between Centralization and Decentralization 8. Municipal Reform in Nova Scotia 9. Municipal Reform in Newfoundland and Labrador: A Tradition of Cautious Evolution 10. Municipal Reform in Prince Edward Island 11. Municipal Reform in New Brunswick: To Decentralize or Not To Decentralize? 12. Municipal Reform in the Northern Territories: Now for Something Different Part III: Comparative Overview 13. Reflections on Municipal Reform
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".