Potential residential spaces for local food production in a suburban municipality
Bibliographic record
Abstract
This case study aimed to examine the potential areas for local food production in the City of Langford, a suburban municipality on southern Vancouver Island, Canada. To this end, initially, different zones of Langford were inspected to identify the areas with potential for growing food. After the selection of the city center, neighbourhood, and hillside/shoreline as three city zones to be used as research cases, the data related to their various spaces, including roofs, balconies, and yards (back or front yards), were collected using field observations and aerial images. The obtained data were then utilized to estimate the area of the places with potential for local food growing. The results demonstrated that the total usable private open spaces in the City of Langford for local food production represents an area between 1.125 km2 and 2.25 km2 in various productivity scenarios. Based on the research findings, around 35% of residential open spaces might provide some areas for local food production in this city. This research also discusses the importance of urban gardening for global economic and social sustainability issues and offered some initiatives to encourage communities to take advantage of the current possibilities for local food production.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".