Advertising expenditures on child-targeted food and beverage products in two policy environments in Canada in 2016 and 2019
Bibliographic record
Abstract
BACKGROUND: The food industry advertises unhealthy foods intended for children which in turn fosters poor diets. This study characterized advertising expenditures on child-targeted products in Canada and compared these expenditures between Quebec, where commercial advertising to children under 13 is restricted, and the rest of Canada, where food advertising to children is self-regulated. METHODS: Advertising expenditures data for 2016 and 2019 for 57 select food categories and five media channels were licensed from Numerator. Products and brands targeted to children were identified based on their nature and the advertising techniques used to promote them. Advertising expenditures were classified as healthy/unhealthy using Health Canada's nutrient profile model. Expenditures per child capita aged 2-12 years were calculated and expenditures from 2016 were adjusted for inflation. Advertising expenditures were described by media, food category, year, and geographic region. RESULTS: Overall, $57.2 million CAD was spent advertising child-targeted products in Canada in 2019. Television accounted for 77% of expenditures followed by digital media (18%), and the food categories with the highest expenditures were candy/chocolate (30%) and restaurants (16%). The totality of expenditures (99.9%-100%) in both Quebec and the rest of Canada in 2016 and 2019 were considered 'unhealthy'. Across all media channels (excluding digital), advertising expenditures were 9% lower in 2019 versus 2016. Advertising expenditures per capita were 32% lower in Quebec ($9.40/capita) compared to the rest of the country ($13.91/capita). CONCLUSION: In Canada, millions are spent promoting child-targeted products considered inappropriate for advertising to children. While per capita advertising expenditures for these products are lower in Quebec compared to the rest of Canada, they remain high, suggesting that Quebec's commercial advertising restrictions directed to children are likely not sufficiently protecting them from unhealthy food advertising.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".