Addressing the call: A review of food justice courses in Canada and the USA
Bibliographic record
Abstract
To address inequality's root causes both within and beyond the food chain, food justice scholars have called for explicit integration of trauma/inequity, land, labour, exchange, and governance into post-secondary education food studies and related fields. This paper explores how instructors of food justice courses (identified by key-word internet search) in Canada and the United States are designing their courses. We collected course syllabi from fifteen institutions to determine key themes related to course content based on weekly topics and readings, resulting in the identification of 16 thematic content areas. We identified seven thematic areas related to course goals (n=49) and eight thematic areas related to learning outcomes (n=123). To clearly distinguish between themes represented in the syllabi, we embedded course goals and learning outcomes into the Understanding by Design instructional design framework, which demonstrates how course goals can be separated into the categories of transfer and meaning, and learning outcomes into declarative and procedural knowledge. We examine content areas in relation to food justice scholarship, focusing on what is present, underrepresented, and absent. In consideration of the Understanding by Design framework, we discuss the need for established goals within which to situate food justice courses, challenges of course scope, value of scaffolding goals and outcomes across programs, and future directions for aligning potential indicators of understanding and identifying effective learning activities. The intended outcome of the paper is to provide current and prospective instructors with greater clarity on how food justice is being taught in order to increase our collective effectiveness in developing student capacities in the field.
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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) | 0.001 | 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 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".