Municipal Mergers: The New City of Toronto Experience THE MOMENTUM FOR CHANGE
Bibliographic record
Abstract
Canada, area had been building for at least 10 years. The only consensus was that, firstly, the status quo was no longer an option and, secondly, throughout any change process, services must continue to be delivered to the residents, businesses and visitors without any interruption. When “change ” finally arrived, it was sudden, with little preparatory time, and it was massive. On Jan. 1, 1998, the new “amalgamated ” City of Toronto was born. As many can attest, the amalgamation process has not always been smooth sailing. In fact, the experience could be likened to a white water rafting adventure: sometimes calm, sometimes rocky, sometimes slower than you anticipated, sometimes a bit faster than you would like, sometimes you get carried along with the flow, sometimes you tip and think you are going under the white water and sometimes you are not sure what is around the next bend. But one thing is for sure—the journey has been an interesting one. The following is a synopsis of our amalgamation experience. GOVERNANCE STRUCTURE HISTORY A new regional government known as Metropolitan Toronto was formed in 1953 as a two-tier federated system that balanced regional and local powers. The new government was given greater powers and responsibilities than had been accorded any municipal government of regional scope in Canada. The lower tier BY W. LES KELMAN comprised 13 local municipalities with elected councils but with mostly reduced responsibilities (see Table 1). In 1967, the number of local municipalities was reduced by amalgamation from 13 to six. The six were the Cities of
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.038 | 0.012 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 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".