Results of Applying the Canadian Proposed Front-Of-Pack Labelling Regulations to Chain Restaurant Menu Items
Bibliographic record
Abstract
Restaurants are subject to far less regulation than packaged foods when it comes to disclosing nutritional information. However, this sector is increasingly prominent in consumer's food purchasing and consumption habits. Health Canada is developing new front-of-package (FOP) warning labels for packaged food and beverage products, which if applied to restaurant foods could help consumers avoid foods high in nutrients of public health concern. The objective of this study was therefore to assess the proportion of menu items that would be required to carry FOP symbols if they were applied to the restaurant sector. Nutrient data for food and beverage menu items (n = 10,950) were collected from the websites of restaurants with ≥20 Canadian outlets in 2016. Each item was assessed according to Health Canada's FOP thresholds for saturated fat, sodium, and sugar to determine eligibility for each warning symbol if the regulations were extended to restaurant foods. Of all eligible menu items, 79% would require ≥1 FOP symbol and 48% would require ≥2. In terms of nutrients, ≥47% of all items would require a sodium or saturated fat warning. 79% of all beverages and desserts would require a sugar warning. When distinguishing between types of restaurants, proportions from fast-food and sit-down establishments were similar overall, but varied by category. The majority of menu items are high in nutrients of public health concern, thus there is an urgent need for regulations that apply to both packaged and restaurant items to improve their nutritional quality and assist consumers in making healthier choices when eating out. Such warning labels could also stimulate product reformulation and the introduction of healthier choices by the restaurant sector. This research was supported by a CIHR Project Operating Grant. KMD was supported by an Endeavour Research Fellowship and a Foundation for High Blood Pressure Research Early Career Transition Grant.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".