Does Banning Carbonated Beverages in Schools Decrease Student Consumption
Bibliographic record
Abstract
In an effort to combat childhood obesity, many schools have banned the sale of carbonated beverages on school grounds. I evaluate the effectiveness of these measures by investigating their impact on household carbonated beverage consumption. I match households in Nielsen Homescan Data to their school district’s carbonated beverage policies over the last 10 years. I use variation across school districts in whether the policy was implemented and the timing of the policy, as well as whether the household has children in the age group included in the policy. I find that when high schools ban the sale of carbonated beverages to students, households with a high school student experiencing the ban increase their consumption of non-diet carbonated beverages by roughly the equivalent of 3.5 cans per month. Increased consumption is greater in the quarter following the policy implementation and appears to persist even a year after the introduction of the ban. I present evidence that the average high school student consumes roughly 4.5 cans of non-diet soda per month in school, when carbonated beverages are available. Thus, the results suggest that the drop in student school consumption is substantially offset by increased household consumption.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".