A Comparison of the Product (Re)formulation Actions and Commitments of the Top Packaged Food and Beverage Companies in Canada
Bibliographic record
Abstract
Canada’s packaged food supply is dominated by energy-dense products high in nutrients of public health concern, increasing obesity and non-communicable disease risk. Many packaged food and beverage companies voluntarily commit to improving the nutritional quality of their products. While monitoring is needed to hold companies accountable for these commitments and thereby prompt improvements, there has been little independent monitoring of their voluntary product (re)formulation efforts in Canada.This thesis aimed to conduct a comprehensive comparison of the product (re)formulation actions and commitments of the top 22 packaged food and beverage companies in Canada. In Study 1, a branded food database was used to compare the nutritional quality of products offered by these companies in 2017, overall and by food category, using multiple measures of nutritional quality. The nutritional quality of products offered by these companies differed significantly overall and by food category, with many products considered less healthy. Study 2 aimed to develop and apply a tool for quantifying the strength of companies’ voluntary recent actions and commitments to improve the nutritional quality of their products. Scores based on the Food Company Reformulation (FCR) tool were low, on average, suggesting that many of Canada’s leading food companies report limited or no action concerning product (re)formulation. Study 3 examined the relationship between the strength of companies’ voluntary product (re)formulation commitments and changes in the nutritional quality of their Canadian products, using companies’ FCR scores and branded food data collected in 2013 and 2017. While some companies improved the healthfulness of their products over this period, many companies’ product portfolios were unchanged or became less healthy from 2013-2017. Moreover, the products of companies reporting stronger voluntary product (re)formulation actions/commitments did not undergo greater improvement in nutritional quality over time, nor were their products significantly healthier. Overall, many of Canada’s leading food companies have not made meaningful improvements to the nutritional quality of their products in recent years; however, there is considerable variation between companies in terms of their product (re)formulation actions and commitments. These findings highlight a need for mandatory government interventions to help improve the healthfulness of Canada’s packaged food supply.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".