A study of four Prince George community gardens: goals, benefits and challenges of public and private community gardens
Bibliographic record
Abstract
Community gardens have become increasingly popular in recent years, and the Canadian city of Prince George, BC is no exemption. Prince George hosts seven community gardens, four of which were the subject of research. Eighteen qualitative interviews were conducted to determine the structures, goals, benefits and challenges facing each of the four community gardens. The structures were quite varied, though the public and private nature of the gardens were the main divisive factor between the gardens. The two public gardens were run by organizations that offered the produce grown in the gardens to passersby, while the two private gardens offered plots to local residents to grow food for themselves. The five goals of the gardens were quite similar, and included social, a place to grow food, address food insecurity, health, and education. Benefits included social, food (food security and sovereignty), personal enjoyment, and education of the participants, especially children. The challenges the gardens faced varied considerably between the public and private gardens. They included theft and destruction, maintenance and labor capacity, awareness, and the overall structure of the garden. A disconnect was often found between the goals and the benefits of the gardens, and the challenges were especially serious in the public gardens. Public gardens should especially be managed carefully as their misdirected goals seem to be inhibiting the work necessary to run the garden. To ensure the sustainability of these important gardens in Prince George, consideration should be made to the structures of the gardens and changes made to the gardens. --Leaf 2.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".