Re-imagining Community Councils in Canadian Local Government
Bibliographic record
Abstract
In 2015, Toronto City Council asked city staff to review community councils as part of the City’s ward boundary review process. Toronto’s ward boundary review realigned the city’s wards, so the City now needs to set new boundaries for community councils. Staff has been directed to report back to Council in 2017 on the “impacts to governance and structure changes to the authority, duties, and function of community councils.” Meanwhile, in November 2016, the Province of Ontario introduced measures to strengthen the use of community councils across Ontario. There is thus a unique opportunity available to re-imagine the authority and use of Toronto’s community councils. In this paper, we review the function and scope of community councils in Canada, including their theoretical underpinnings and Toronto’s community council structure. We make three recommendations to strengthen Toronto’s community council network. First, we recommend redefining what is considered to be a “local” or “citywide” matter, thereby allowing community councils to examine a greater range of issues. Second, we argue that the City should expand its delegation to community councils, and thereby take more issues off the agenda of City Council. Finally, we propose allowing residents to serve directly on community councils.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.026 | 0.059 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".