Municipal Reform in Canada: Reconfiguration, Re-Empowerment, and Rebalancing
Bibliographic record
Abstract
Municipal Reform in Canada: Reconfiguration, Re-Empowerment, and Rebalancing, Joseph Garcea and Edward C. LeSage, Jr., eds., Toronto: Oxford University Press, 2005, pp. ix, 350. This book will be an essential reference for students of local government in Canada. It deals with the most recent period of municipal reform, from 1990 onwards. There are chapters on each of the ten provinces, plus a combined chapter on the northern territories. The editors establish an analytical framework for the book in their introduction, and then try to bring things together in a long concluding chapter. The individual chapters differ somewhat in approach, but the editors were fairly successful in getting the contributors to keep to a common analytical framework. Reading the whole book straight through is a bit of a slog, because there is so much detail; on the other hand, it is handy to have all this material collected together. It will stimulate useful reflection, as much about what is not here as what is.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.020 | 0.020 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.002 | 0.005 |
| 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".