The physical activity and nutrition-related corporate social responsibility initiatives of food and beverage companies in Canada and implications for public health
Bibliographic record
Abstract
Background: As diet-related diseases have increased over the past decades, large food companies have come under scrutiny for contributing to this public health crisis. In response, the food industry has implemented Corporate Social Responsibility (CSR) initiatives related to nutrition and physical activity to emphasize their concern for consumers. This study sought to describe the nature and targeted demographic of physical activity and nutrition-related CSR initiatives of large food companies in Canada and to compare companies who participate in the Canadian Children’s Food and Beverage Advertising Initiative (CAI), a self-regulatory initiative aimed at reducing unhealthy food advertising to children, with non-participating companies. Methods: A cross-sectional study was conducted in 2016. Thirty-nine large food companies, including 18 participating in the CAI, were included in the study. The webpages, Facebook pages and corporate reports of these companies were surveyed to identify CSR initiatives related to nutrition and physical activity. Initiatives were then classified by type (as either philanthropic, education-oriented, research-oriented or other) and by targeted demographic (i.e. targeted at children under 18 years or the general population). Differences between CAI and non-CAI companies were tested using chi-square and Mann-Whitney U tests. Results: Overall, 63 CSR initiatives were identified; 39 were nutrition-related while 24 were physical activity-related. Most (70%) initiatives were considered philanthropic activities, followed by education-oriented (20%), research-oriented (8%) and other (2%). Almost half (47%; n = 29) of initiatives targeted children. Examples of child-targeted initiatives included support of school milk programs (n = 2), the sponsorship of children’s sports programs (n = 2) and the development of educational resources for teachers (n = 1). There were no statistically significant differences in the number of CSR initiatives per company (CAI: Mdn = 1, IQR = 3; non-CAI: Mdn = 0, IQR = 2; p = .183) or the proportion of child-targeted initiatives (CAI: 42%; non-CAI: 54%; p = .343) between CAI and non-CAI companies. Conclusion: Food companies, including many that largely sell and market unhealthy products, are heavily involved in physical activity and nutrition-related initiatives in Canada, many of which are targeted to children. Government policies aimed at protecting children from unhealthy food marketing should consider including CSR initiatives that expose children to food company branding.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".