Roots, Tendrils, Sprouts and Shoots: A Case Study of Parkallen’s Community Garden, a permaculture project
Bibliographic record
Abstract
The first growing season of Edmonton’s Parkallen Community Garden began in Spring 2012. We transformed an unused strip of lawn bordering our hockey rink into a loamy, thriving “edible food forest” of corn, beans, squash, kale, tomatoes, carrots, potatoes, apple trees, and mammoth sunflowers. It is unlike most community gardens in that individual plots are not tended by individual gardeners; rather, the PCG is tended communally, by the community. The garden is open and accessible to the community, always, and all are welcome there, from the toddler whose only contribution is to chomp on a snowpea and water a dandelion, to the senior who wants to plant a tree in his community that he knows will outlive him. Hundreds of Parkallen residents have planted something, admired something, or munched on something there. In its first year Parkallen’s garden won The City of Edmonton’s top community gardening award from Communities in Bloom. This article is a case study of the Parkallen Community Garden. Through the lenses and observations of the author, it details how Parkallen’s permaculture design came, literally, to fruition and how permaculture has been interpreted and how it informs our garden and our gardening community.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".