Examining the effectiveness of promotional nudges increasing plant-based food choices in a post-secondary education dining hall: a pilot study
Bibliographic record
Abstract
Abstract Objective: To evaluate nudge strategies that increase the consumption of plant-based foods, defined as vegetarian or vegan food items, compared with meat-based options in post-secondary dining hall settings. Design: A pilot study. Setting: This study took place in the University of British Columbia Vancouver Campus’s Gather Dining Hall (GDH) over a 6-week intervention period and two control periods. The intervention incorporated several nudges (proportion increases, item placement, taste-focused labelling, Chef’s featured special verbal prompts, social media and promotional posters) into the menu and dining hall area with the goal of increasing the purchases of plant-based items. Sales data from meals that were purchased during the intervention period were compared with sales data from the two control periods. Participants: Students and staff who purchased meals in the GDH. Results: The proportion of plant-based items sold significantly increased during the intervention period (56·7 %; P < 0·01) compared with the last 6 weeks of term one (53·6 %) and the first 6 weeks of term two (53·4 %). The proportion of plant-based ‘main’ menu items was significantly higher in the intervention period (46·4; P < 0·01) when compared with the last 6 weeks of term one (40·9 %) and the first 6 weeks of term two (41·7 %). Conclusions: The combination of nudges was effective at significantly increasing the selection of plant-based options over meat-based options in a post-secondary dining hall setting.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".