Canada’s new Healthy Eating Strategy: Implications for health care professionals and a call to action
Bibliographic record
Abstract
Nearly two-thirds of all deaths worldwide are from noncommunicable chronic diseases, with a similar proportion in Canada.According to the Global Burden of Disease Study, unhealthy eating is the leading risk for death and the second leading risk for disability in Canada.It is clear that to adequately address this major health issue, we need a comprehensive approach that includes strong governmental policy.In 2016, the Canadian government released its Healthy Eating Strategy, for which updating Canada's Food Guide was a key element.The government released the first wave of documents (including the new food guide and dietary guidelines) in January 2019, with the healthy eating patterns guidance to follow later in 2019.Much of this work aligns with a number of policies that have been developed and adopted by the Canadian health and scientific organizations that are members of the Canadian Hypertension Advisory Committee.As such, the current editorial is a call to action for the health care and scientific community, both individuals and organizations, to ensure they have policies consistent with and supportive of those that have been developed through the Hypertension Advisory Committee collaboration and to actively participate in providing input and feedback on the Healthy Eating Strategy through the Health Canada Stakeholder Registry.BOX 1 Useful websites Health Canada's healthy eating strategy: https://www.canada.ca/en/services/health/campaigns/vision-healthy-canada/healthy-eating.html
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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 | 0.042 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.020 | 0.020 |
| Scholarly communication | 0.025 | 0.011 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.036 | 0.031 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
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".