A need for multi-sector and multi-pronged solutions to address the many barriers inhibiting change from unhealthy food environments in publicly funded recreation facilities: a mixed-method study
Bibliographic record
Abstract
Public recreation facilities are preferred gathering places for families to participate in physical, social, intellectual, and creative pursuits, and the importance of food environments in these facilities is gaining recognition. Evidence from other Canadian jurisdictions describes such food environments as unsupportive of health, which contradicts national recreation priorities to have healthy choices as the easy choices. This study aimed to characterize food environments in a convenient sample of Saskatchewan public recreation facilities. A convergent/parallel mixed methods study design used quantitative methods to determine the healthfulness of concession stands and vending machines and qualitative methods to examine barriers and facilitators to healthy eating in facilities. The results found that 5% of concession main dishes were defined as healthy and packaged foods/beverages in concession stands and vending machines were defined as Offer Most Often 6% and 8% of the time, respectively, according to Saskatchewan Nutrition Standards. Reported barriers to healthy eating were more than twice as prevalent as facilitators. To align with population health recommendations in Saskatchewan, food environments in public recreation facilities require immediate attention. The results and recommendations can be used to build collective action to address the problem and as a benchmark to measure change. Novelty: Only 5% of concession main dishes were defined as healthy. Only 6% of packaged foods and beverages in concessions, and 8% in vending, were defined as Offer Most Often. Reported barriers to healthy eating were more than twice as prevalent as facilitators, resulting in a current state that is difficult to change.
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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 | 0.084 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".