Global benchmarking of children's exposure to television advertising of unhealthy foods and beverages across 22 countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Restricting children's exposures to marketing of unhealthy foods and beverages is a global obesity prevention priority. Monitoring marketing exposures supports informed policymaking. This study presents a global overview of children's television advertising exposure to healthy and unhealthy products. Twenty-two countries contributed data, captured between 2008 and 2017. Advertisements were coded for the nature of foods and beverages, using the 2015 World Health Organization (WHO) Europe Nutrient Profile Model (should be permitted/not-permitted to be advertised). Peak viewing times were defined as the top five hour timeslots for children. On average, there were four times more advertisements for foods/beverages that should not be permitted than for permitted foods/beverages. The frequency of food/beverages advertisements that should not be permitted per hour was higher during peak viewing times compared with other times (P < 0.001). During peak viewing times, food and beverage advertisements that should not be permitted were higher in countries with industry self-regulatory programmes for responsible advertising compared with countries with no policies. Globally, children are exposed to a large volume of television advertisements for unhealthy foods and beverages, despite the implementation of food industry programmes. Governments should enact regulation to protect children from television advertising of unhealthy products that undermine their health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it