University Students Harvesting the Benefits of a Garden Laboratory
Bibliographic record
Abstract
Community gardens (CG) are areas of land where individuals or groups grow food in single or shared plots, typically in an urban setting, providing fresh produce, urban greening, and opportunities to socialize and improve the community. The purpose of this descriptive study was to introduce a CG laboratory (lab) as part of an introductory foods course within a nutrition program and explore how the lab influenced students’ learning and overall experiences. Forty-one students, 2 lab instructors, and 3 student volunteers who tended the CG participated in the survey. Survey analysis revealed 4 interrelated themes: (i) connection and exposure, (ii) food preparation, (iii) benefits of using local food, and (iv) explicit learning. Overall, the lab fostered multiple types of individual and relational learning involving the acquisition of course content and food literacy skills. The CG was valued by students as a curriculum component as well as opportunities for personal growth and development. With the growing importance of food systems knowledge to the profession, CG may act as a site for embodied forms of learning in nutrition programs.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".