The Time is Ripe: New Financial Tools for the City of Toronto’s Parkland Dedication Rate
Bibliographic record
Abstract
Developments in Ontario municipalities convey parkland under Section 42 of the Planning Act. Cash-in-lieu is contributed for parkland acquisitions when parkland cannot be conveyed. The City of Toronto had amassed $237,620,212 in cash-in-lieu reserve funds as of December 31, 2019. Complex spending rules hamper the use of existing funds. Municipal officials estimate that by 2034 there will be 25 m2 of parkland per person in Toronto compared with 28 m2 in 2016. Washington, D.C. has a green space standard of 38 m2 per person. The Nature Conservancy of Canada and Rally Assets estimates an annual national biodiversity funding gap of CAD 19.5-26 billion. The use of new financial tools for biodiversity conservation is catching on in the financial and philanthropic sectors. This MRP recommends amending existing rules to facilitate the use of cash-in-lieu reserve funds, to pursue new financial tools to acquire parkland, and to convene stakeholders across sectors.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.005 |
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".