The University of British Columbia healthy beverage initiative: changing the beverage landscape on a large post-secondary campus
Bibliographic record
Abstract
OBJECTIVE: Environmental interventions are more effective at changing nutrition behaviour than educational campaigns alone. As part of their health promotion efforts, the University of British Columbia (UBC) developed the Healthy Beverage Initiative (HBI) to ultimately reduce the consumption of sugar-sweetened beverages (SSB) on campus. We describe the development, implementation, preliminary evaluation and future of the HBI. DESIGN: Naturalistic observation of environmental changes to induce behaviour change. SETTING: Large urban research university campus. PARTICIPANTS: University community members and campus visitors. RESULTS: Three main activities have been implemented since the initiation of the UBC HBI: renegotiation of the cold beverage agreement, a media campaign to promote tap water consumption and the removal of SSB from select retail locations on campus (residence dining hall). No significant loss of revenue was observed following the removal of SSB from a residence dining hall compared with similar locations. Compensatory purchasing behaviour of SSB was not observed at the closest retail locations where they were still available. After the removal of SSB, ~75% of survey respondents were not aware that the beverages had been removed. CONCLUSIONS: The implementation of the HBI has met little resistance from the UBC community. The removal of SSB from residence dining locations did not result in any significant revenue loss or compensatory purchasing behaviour. This suggests that environmental intervention initiatives appear to be a viable option that may reduce SSB consumption on post-secondary campuses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".