Community gardens and urban agriculture: Healthy environment/healthy citizens
Bibliographic record
Abstract
Studies are showing that urban community gardening can improve people's psychological and physiological health in myriad ways. Community gardens increase social capital, provide opportunities for altruism, and create accessible and sustainable food sources in urban environments. The purpose of this study was to explore the mental, social, and physical health benefits of participation in an urban community garden in Edmonton, Canada. A focused ethnography was conducted with surveys and semi-structured interviews. Surveys were sent to volunteers and customers of the Green and Gold Garden (GGG). This was followed by focus group interviews with eight volunteers and four customers. The interview format comprised open-ended questions that encouraged participants to share their perceptions of the health and well-being benefits from being at the GGG. Data were coded via inductive coding, and subsequently categorized into themes via an iterative, reflective process. Four health-related themes were generated from thematic analysis: physical health, social health, mental/emotional health, and connection to the global community. Spending time at the GGG improved the respondents' mental health, even during the COVID-19 pandemic, as they reported feelings of altruism, serenity, and connection with nature. Their social health was improved through gathering with other garden members in a sheltered urban green space within the city limits. This study supports the idea that participation in an urban community garden confers health benefits and engenders a greater awareness of, and appreciation for, the local environment and expands one's scope of care to incorporate planetary health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".