Lobbying and nutrition policy in Canada: a quantitative descriptive study on stakeholder interactions with government officials in the context of Health Canada’s Healthy Eating Strategy
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The political activities of industry stakeholders must be understood to safeguard the development and implementation of effective public health policies. METHODS: A quantitative descriptive study was performed using data from Canada's Registry of Lobbyists to examine the frequency and governmental target of lobbying that occurred between various types of stakeholders (i.e., industry versus non-industry) and designated public office holders (DPOH) regarding Health Canada's Healthy Eating Strategy, from September/2016 to January/2021. Initiatives of interest were revisions to Canada's Food Guide, changes to the nutritional quality of the food supply, front-of-pack nutrition labelling and restrictions on food marketing to children. RESULTS: The majority of registrants (88%), and corporations and organizations (90%) represented in lobbying registrations had industry ties. Industry-affiliated stakeholders were responsible for 86% of communications with DPOH, interacting more frequently with DPOH of all ranks, compared to non-industry stakeholders. Most organizations and corporations explicitly registered to lobby on the topic of marketing to children (60%), followed by Canada's Food Guide (48%), front-of-pack nutrition labelling (44%), and the nutritional quality of the food supply (23%). The food and beverage industry, particularly the dairy industry, was the most active, accounting for the greatest number of lobbying registrations and communications, followed by the media and communication industry. CONCLUSIONS: Results suggest a strategic advantage of industry stakeholders in influencing Canadian policymakers. While some safeguards have been put in place, increased transparency would allow for a better understanding of industry discourse and help protect public health interests during the policy development process.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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