Home Food Gardening in Canada in Response to the COVID-19 Pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The lack of academic attention that home food gardening has received in Canada and the United States is surprising, given the many demonstrated benefits of community gardening programs, including increased community cohesion and resilience. The aim of the exploratory study is to explore the current surge in home food gardening and its relationship to the COVID-19 pandemic. A national survey was conducted, consisting of 43 main questions, asking respondents about their home life and food provisioning during COVID-19, the physical characteristics of their food gardens, and their attitudes and beliefs concerning home food production. Survey results show that 51% of respondents grow at least one type of fruit or vegetable in a home garden. Of those, 17.4% started growing food at home in 2020 during COVID-19 pandemic. To gain more insight into just how significant a cause the pandemic lockdown was on home food gardening, follow-up surveys and policy recommendations are suggested.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it