Prompted awareness and use of <i>Eating Well with Canada's Food Guide</i>: a population‐based study
Bibliographic record
Abstract
BACKGROUND: Little is known about the awareness of Canada's Food Guide (CFG). The present study aimed to report the general and specific awareness of CFG recommendations among adults in Alberta, Canada. METHODS: For this cross-sectional study, respondents (aged >18 years) from randomly selected households completed a telephone survey. Questions pertaining to CFG, physical activity, and vegetable and fruit consumption were included. Logistic regression determined associations between demographic characteristics and awareness of CFG. RESULTS: Thousand two hundred and ten Albertans (50% female, mean age 50.5 years) responded. Most [86.5%; 95% confidence interval (CI) = 84.6-88.4] indicated being generally aware of CFG when prompted and 82.5% were aware of specific CFG recommendations. There were no differences in age between those generally aware and unaware of CFG. Female sex [odds ratio (OR) = 3.6; 95%CI = 24-5.4], Caucasian ethnicity (OR = 3.7; 95% CI = 2.3-5.8), income ≥ Canadian $100 000 per annum (OR = 1.6; 95% CI = 1.1-2.3), reporting ≥5 vegetables and fruit per day (OR = 2.1; 95% CI = 1.4-3.2), exceeding recommended levels for physical activity (OR = 2.0; 95% CI = 1.3-2.9) and perception of current weight as healthy (OR = 1.8; 95% CI = 1.2-2.8) were associated with an awareness of CFG. CONCLUSIONS: Sex, ethnicity and income were associated with general awareness of CFG. Future studies could explore the relationship between awareness and other health-related behaviours.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".