Food marketing to children in Canada: a settings-based scoping review on exposure, power and impact
Bibliographic record
Abstract
INTRODUCTION: Food marketing impacts children's food knowledge, behaviours and health. Current regulations in Canada focus on restricting promotional aspects of food marketing with little-to-no consideration of the places where children experience food. Understanding food marketing in children's everyday settings is necessary to protect children. This scoping review describes the current literature on food marketing to children in Canada by setting. METHODS: The author searched databases for Canadian research on children's exposure to food marketing, and the power and impact of food marketing to children (2-17 years) across settings, and on how current regulations may mediate the effect of food marketing on children. Peer-reviewed studies in English, published between 2000 and 2016, were included. RESULTS: Twenty-five studies documented children's exposure to food marketing and its power and/or impact on them in homes (via television, or online) (n = 12), public schools (n = 1), grocery stores (n = 8), fast food restaurants (n = 2), and in general (n = 2). Research trends suggest that unhealthy foods are targeted at children using multiple promotional techniques that overlap across settings. Several research gaps exist in this area, leading to an incomplete, and potentially underestimated, picture of food marketing to children in Canada. Available evidence suggests that current Canadian approaches have not reduced children's exposure to or the power of food marketing in these settings, with the exception of some positive influences from Quebec's statutory regulations. CONCLUSION: The settings where children eat, buy or learn about food expose them to powerful, often unhealthy food marketing. The current evidence suggests that "place" may be an important marketing component to be included in public policy in order to broadly protect children from unhealthy food marketing. Organizations and communities can engage in settings-based health promotion interventions by developing their own marketing policies that address the promotion and place of unhealthy food and beverages.
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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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.029 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".