How Can Dietitians Leverage Change for Sustainable Food Systems in Canada?
Bibliographic record
Abstract
Purpose: In this paper, we begin to set out language defining sustainable food systems (SFS) in Canada, through the voices of dietitians, and identify leverage points where dietitians can affect change. Methods: Dietitians of Canada members were invited to a Delphi Inquiry process; questions explored a vision of SFS in Canada, barriers to that vision, and actions. Results were independently analysed by 2 members of the research team who used the Framework for Strategic Sustainable Development to structure the data. Results: Fifty-eight members participated. The resultant vision describes a future food system in 15 thematic areas of the social and ecological systems. Barriers are described according to how they undermine sustainability. High-leverage actions areas included: (i) facilitating knowledge development within the profession and public, (ii) influencing organizational policy to support SFS, and (iii) and influencing public policy. Approaches to such action included: (i) facilitating cross-sectoral collaboration and (ii) applying reflexive approaches. Conclusions: This research suggests a multidimensional understanding of food systems sustainability among dietitians. The vision provides some language to describe what dietitians mean by SFS and can be used as a compass point to orient action. Action areas and approaches have the potential to drive systemic change while avoiding unintended consequences.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".