Healthy vending contracts: Do localized policy approaches improve the nutrition environment in publicly funded recreation and sport facilities?
Bibliographic record
Abstract
This study explored the influence of healthy vending contracts (HVC) on the nutritional quality of vending machine products in 46 Canadian publicly funded recreation and sport facilities. A quasi-experimental comparison design was used to examine the difference in nutritional quality of snack and beverage vending machine products at baseline (December 2015–May 2016) and 18-month follow-up. Staff Surveys assessed facility contract type (HVC or conventional) and vending machine audits identified product nutritional quality. Products were categorized by provincial guidelines as Do Not Sell (DNS), Sell Sometimes (SS) or Sell Most (SM). ANOVA compared categories cross-sectionally (HVC vs conventional) and repeated measures ANOVA compared them longitudinally (HVC-HVC, vs conventional-conventional and conventional-HVC). Approximately one quarter of contracts (24% beverage and 28% snack) had health stipulations at baseline or follow-up. Cross-sectionally, facilities with HVC at any time period had significantly lower percentage DNS (beverage: 56% vs 73%, p = 0.001; snack: 55% vs 85%, p < 0.001), higher SS (beverage: 24% vs 14%, p = 0.003; snack: 35% vs 12%, p < 0.001) and higher SM Products (beverage: 21% vs 13%, p = 0.030; snack: 10% vs 3%, p < 0.003). Longitudinally, facilities with consistent HVC or that changed to HVC showed greater decreases in DNS products over time (p < 0.050). Although less healthy products were still highly prevalent, facilities with HVC or that changed to HVC had fewer unhealthy products available in their vending machines over time compared to those without HVCs. Healthy vending contracts appear to be an effective change strategy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".