Environmental health assessment of communities across Canada: contextual factors study of the Canadian Alliance for Healthy Hearts and Minds
Bibliographic record
Abstract
Rationale: Cardiovascular risk varies across communities in Canada. Community-level differences in contextual factors may influence risk factor development.Methods: We audited urban and rural Canadian communities using a standardized instrument to collect objective measures of demographic, public transport, tobacco, grocery, alcohol, and healthful restaurant options. We duplicated 209 audits to assess reliability.Results: Of 2074 communities audited between 2014 and 2016, 83.5% were urban. Provincial and urban-rural differences exist in fruit and vegetable availability. Rural communities face higher food prices, are subject to more seasonal variation in fruit and vegetable selection, and generally see less promotion of healthy choices and nutritional information in restaurants than urban communities. In-store advertising for sweet drinks and junk food is more frequent than advertisements for tobacco products. Cigarette prices are lower and variety higher in urban than rural communities, and lowest in central Canada. Alcohol prices are lowest in Quebec. The intra-rater reliability of the audits was high. We created an on-line map for public use.Conclusions: Provincial and urban-rural differences exist for contextual determinants of health. Public health and built environment professionals and government officials should use these data to develop unified federal and provincial strategies to reduce Canada’s chronic disease burden.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".