Planting seeds of community-engaged pedagogy: Community health nursing practice in an intergenerational campus-community gardening program
Bibliographic record
Abstract
As part of a participatory action research (PAR) study, nursing student participants collaborated with faculty, along with older adults, people with mixed abilities, and preschool aged children in order to 'sow the seeds of social change' and grow a campus community gardening project. The focus of this article is on the community-engaged pedagogy within a community health nursing practice course that supported student learning. Insights were gleaned over the course of four academic semesters (and four student cohort groups) with students as co-developers of the campus-community garden and participants in the PAR. Key themes emerged from student participants in the PAR process including: (1) planning in community to "think global, act local"; (2) discovering 'the people in your neighbourhood' as socially just partnerships; (3) revisiting landscapes of social inclusion; and (4) reflecting on "humble togetherness" across generational gaps. The findings showcased here attest to how community-engaged pedagogy, in conjunction with PAR, can facilitate student learning outside of traditional settings and grow social inclusion, intergenerational connection, and social justice.
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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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.014 |
| 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".