Awareness and Knowledge of Recommendations from Canada's Food Guide
Bibliographic record
Abstract
PURPOSE: To examine use and content knowledge of Canada's Food Guide recommendations. METHODS: A total of 1048 intercept exit surveys were conducted with adults who had purchased food that day at 2 hospital cafeterias in Ottawa, Ontario. RESULTS: Most respondents (85.9%) reported looking at Canada's Food Guide over their lifetime; however, less than half reported looking at the food guide in the past year. Milk and Alternatives were the most commonly recalled food group (80.1%) and Grain Products were least commonly recalled (66.0%). Of the entire sample, 42.8% correctly recalled all 4 food groups. Overall, 0.8% correctly recalled the correct number of servings for all 4 food groups. Females, younger respondents, white respondents, respondents with higher annual income, and respondents who had reported looking at Canada's Food Guide recalled more food groups (P < 0.05 for all). CONCLUSIONS: Despite high levels of awareness, the study found relatively low levels of reported use and very low levels of knowledge of Canada's Food Guide, particularly among population subgroups that face health disparities. Improving awareness, knowledge, and use of Canada's Food Guide may contribute to improving the nutrition profile of Canadians.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".