Restricting Marketing of Unhealthy Foods: Should General Internists Engage?
Bibliographic record
Abstract
Unhealthy diet is the leading risk for death, years of life lost, and disability, causing an estimated 65,722 deaths and 864,032 life years lost in Canada in 2010. 1 Although the causes of unhealthy diet are complex, unhealthy eating habits start early in life, and unhealthy food and beverage marketing to children is consistently associated with unhealthy dietary behaviours and childhood obesity. Although there have been recommendations from the World Health Organization (WHO) and the United Nations urging countries to restrict such marketing to children as a population strategy to improve diet, the food industry continues to direct millions of marketing dollars to increase the sales and consumption of the very foods that contribute to disease burden. While many countries have heeded the WHO recommendations, in Canada, outside of Quebec, the food industry largely self-regulates its marketing of unhealthy food to children, with no government monitoring or oversight. The result is that Canadian children are extensively exposed to marketing of unhealthy food products that would not be allowed in several other countries.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.013 | 0.007 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".