Collaborative Course Design: A Contribution Toward a Radical Food Systems Pedagogy
Bibliographic record
Abstract
The nascent (sub)field of critical food systems pedagogy is developing, in part, through a critique of conventional approaches to teaching and learning about food and agriculture. Within this fertile context, scholars and practitioners have been reckoning with what and how to teach for more just and sustainable worlds through a distinctly critical food systems pedagogy. We draw inspiration from this work, and build on it through experimentation with how we design what we teach. Our specific, modest intervention focuses on engaging students, in conversation, in the process of curriculum co-design. We explore this through a case study of co-designing The Edible Campus, a combined 4th year and graduate level course. We provide insight into the co-design process, outline how the co-design process shaped the course, and summarize challenges of the co-design process.
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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 | 0.032 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".