Can we eat our way to a healthy and ecologically sustainable food system?
Bibliographic record
Abstract
The food system is a major contributor to climate change, biodiversity loss, eutrophication and deforestation. This article examines national dietary guidelines as a way to shift dietary patterns in the population toward diets that continue to promote health while being more ecologically sustainable. While some sustainability principles may be inherent in the 2007 Canada’s Food Guide (e.g., an emphasis on plant-based foods), these were not made explicit. As Health Canada undertakes a revision of its national dietary guidance, a unique opportunity exists to situate dietary guidelines within the broader context of Canada’s first-ever national food policy. Coherence between these two policies has the potential to position the role of diets as a core link between food systems and both human and ecological health. This paper explores the possibilities of advancing sustainability principles within Canadian national dietary guidelines by drawing on evidence-based literature and key sustainability messages within dietary guidelines from four countries that have integrated many of these principles. Lessons and perspectives from international experiences on incorporating environmental sustainability into dietary guidelines are described including: influence of the food industry; cross-sector collaboration and alliances; civil society participation; and “win-win” messages. Application of these lessons to Canada, followed by opportunities to advance the incorporation of sustainability principles within the country’s national dietary guidelines are then proposed.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| 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".