Confronting Colonialism in Canadian Dietetics Curricula
Bibliographic record
Abstract
Many Canadian universities have committed to becoming more accountable to Indigenous Peoples by confronting the systemic, historical, and ongoing colonialism and anti-Indigenous racism that shape their campuses. In this Perspective in Practice piece, we invite the field of dietetics to consider how colonialism has shaped dietetics research, teaching, and practice. We also consider how we might transform the field of dietetics in ways that accept settler responsibility for interrupting racism and colonial harm; support the resurgence of Indigenous food and health practices; and recognise the connections between struggles to ensure that Indigenous Peoples can access culturally appropriate food and health care, and struggles for Indigenous sovereignty and self-determination. We do this by reviewing the history of the dietetics field, examining critical responses to existing Indigenisation and decolonisation efforts, and reflecting on recent changes to required dietetics competencies. We argue that curricula in dietetics programmes must teach the history of the colonial food system and equip students to identify and interrupt the individual and institutional colonial dynamics that contribute to the ongoing dispossession of Indigenous Peoples' lands and food sources and negatively impact Indigenous patients.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.013 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".