Could Toronto Provide 10% of its Fresh Vegetable Requirements from Within its Own Boundaries? Part II, Policy Supports and Program Design
Bibliographic record
Abstract
Urban agriculture in Toronto largely focuses on self-provisioning, but it could be scaled up significantly. Our findings in an earlier paper indicate that the supply of land is not an insurmountable barrier. Rather, other more subtle impediments exist, including taxation systems and structures that assume agriculture is a strictly rural activity; inadequate sharing of knowledge among urban producers; limited access to soil, water, and seeds; and the lack of incentives to attract landowners and foundations to provide financial or in-kind support.The potential exists to develop urban agriculture so that it supplies 10% of the city's commercial demand for fresh vegetables. Scaling up to this level requires significant policy and program initiatives in five key areas: Increasing urban growers' access to spaces for production; putting in place the physical infrastructure and resources for agriculture; integrating local food production into the food supply chain; creating systems for sharing knowledge; and creating new models for governance, coordination, and financing. Our recommendations, while focusing on Toronto, offer lessons for those currently attempting to strengthen urban agriculture in other cities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".