The honeymoon is over: Proposed Bill 68 and its implications for infrastructure planning in Ontario Municipalities
Bibliographic record
Abstract
In November 2016, the Ontario government tabled Bill 68, Modernizing Ontario’s Municipal Legislation Act. This bill, if passed, will introduce a series of reforms to the Municipal Act and the Planning Act which outline the legislative, administrative, and financial responsibilities of Ontarian municipalities. There are 3 major provisions proposed in this Bill. First, municipalities will be required to have a policy pertaining to protection and enhancement of their tree canopy and natural vegetation. Second, the proposed amendments would authorize Cities to pass a by-law respecting the protection or conservation of the environment that requires buildings to be constructed with green roofs. Third, municipalities will have clearer jurisdiction to regulate with respect to climate change and energy conservation. If the Bill is passed into Law, it is likely to trigger changes in Ontario's asset management planning regulation system and will transform infrastructure investment and planning, while changes to the Planning Act and the Municipal Act will expand municipal powers to engage in long-term energy planning and to adopt by-laws on energy and climate change. The proposed changes require commitment from both elected officials and municipal administration coupled with continued federal government support through infrastructure grants to complement existing sources of local revenue.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.009 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".