The New Governmental Structure Of Toronto And Its Relevance For The Economic And Social Environment Of The 21st Century
Bibliographic record
Abstract
The present government of Ontario has made a number of major changes in the way that municipalities are governed and financed. Some municipalities have been forced to amalgamate despite opposition from their residents. Ontario has also redistributed the responsibilities of the province and the municipalities through the Local Service Realignment Program (LSR). This program is commonly refereed to as downloading. Other major changes include the use of market value assessment for property tax evaluation and the transfer of education funding to the province from the local school boards. This paper is concerned with two aspects of these changes. Are megacities less costly to operate than many small municipalities in a large urban area? The recent amalgamation of the City of Toronto is used to examine this question. Since the amalgamation occurred in 1998, the new city is still adjusting to the changes and only preliminary conclusions can be drawn about this question. The second question is concerned with the impact of downloading on the municipalities. The experience of the new City of Toronto is again used to examine this question.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".