Alcohol lobbying in Canada: a quantitative analysis of the federal registry of lobbyists
Bibliographic record
Abstract
Although alcohol is a leading cause of health and social harms in Canada, policies directed at alleviating the public health burden created by alcohol are rarely adopted and often reversed. This study analyses alcohol-related policy lobbying activity to better understand how lobbying might impact policy development in Canada. This was deemed not human subjects research. A cross-sectional analysis was conducted using data from the federal Canadian Registry of Lobbyists to characterize the frequency and nature of alcohol industry and public health lobbying activities between May 2022 and May 2023. In this period, there was substantially more lobbying activity by alcohol industry representatives compared to public health stakeholders. Over three-quarters of lobby groups represented alcohol industry organizations (n = 13) compared to public health organizations (n = 4), with industry recording a majority of registered lobbyists (81.3%), meetings reported (66.2%), and number of officials lobbied (71.2%). Alcohol industry organizations predominantly lobbied bureaucrats in policy making/governance roles (54.2% of industry meetings), while public health stakeholders mainly lobbied legislators (60.4% of public health meetings). The alcohol industry's dominance in federal lobbying activities may enable corporate influence over alcohol policy development and undermine public health approaches. The nature of lobbying in Canada has international implications for the regulation of a product that is an important commercial determinant of health, showing the potential role lobbying may play in weakening alcohol regulation.
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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 | 0.001 | 0.001 |
| 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 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".