The Impact of Crunchy Wednesdays on Happy Meal Fruit Orders: Analysis of Sales Data in France, 2009–2013
Bibliographic record
Abstract
OBJECTIVE: Beginning in September, 2010, all McDonald's restaurants in France offered free fruit with every Happy Meal sold on the first Wednesday of the month. Sales data were used to determine the impact of free fruit promotion on the proportion of regular Happy Meal fruit desserts sold. METHODS: Trend analyses examined the proportion of fruit desserts for 2009-2013. Analyses also compared fruit orders on Crunchy Wednesdays with other weekdays. RESULTS: Happy Meal fruit desserts rose from 14.5% in 2010 to 18.0% in 2011 and to 19.4% in 2013 (P < .001). More Happy Meal fruit desserts were ordered on Crunchy Wednesdays compared with other weekdays (P < .001). Orders of cherry tomato sides and water as a beverage on Crunchy Wednesdays were unaffected. CONCLUSIONS AND IMPLICATIONS: Based on sales transactions data across multiple years, this study provides evidence of the long-term effectiveness of menu promotions aimed at increasing children's consumption of vegetables and fruit.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".