Centering Equity in Sustainable Food Systems Education
Bibliographic record
Abstract
Sustainable food systems education (SFSE) is rapidly advancing to meet the need for developing future professionals who are capable of effective decision-making regarding agriculture, food, nutrition, consumption, and waste in a complex world. Equity, particularly racial equity and its intersectional links with other inequities, should play a central role in efforts to advance SFSE given the harmful social and environmental externalities of food systems and ongoing oppression and systemic inequities such as lack of food access faced by racialized and/or marginalized populations. However, few institutional and intra-disciplinary resources exist on how to engage students in discussion about equity and related topics in SFSE. We present perspectives based on our multi-institutional collaborations to develop and apply pedagogical materials that center equity while building students' skills in systems thinking, critical reflection, and affective engagement. Examples are provided of how to develop undergraduate and graduate sustainable food systems curricula that embrace complexity and recognize the affective layers, or underlying experiences of feelings and emotions, when engaging with topics of equity, justice, oppression, and privilege.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.021 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".