An examination of municipal efforts to manage brownfields redevelopment in Ontario, Canada
Bibliographic record
Abstract
Since the mid-1990s, the reuse of brownfield properties for urban intensification has emerged as a core strategy in government efforts to remediate pollution and support renewal, regeneration, and retrofitting. While upper levels of government in Canada engaged in early efforts to devise policies, programs, and funding strategies to support redevelopment, the job of overseeing it has fallen mainly to local governments. This paper investigates the role of municipalitiesin Ontario, Canada’s most populous and industrialized province, in managing and facilitating brownfields redevelopment. Survey data from 43 municipalities, coupled with information gathered from six site visitations and provincial information, reveal that despite common goals, tools, and approaches put forward by Ontario municipalitiesin their Community Improvement Plans, the management of planning, funding, and redevelopment issues continues to be a challenge for many, resulting in some very proficient municipalities and numerous hopeful ones with limited capacity to address this demanding issue.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".