Content Analysis of the Corporate Social Responsibility Practices of 9 Major Cannabis Companies in Canada and the US
Bibliographic record
Abstract
Importance: The cannabis industry has sought to normalize itself and expand its markets in the 21st century. One strategy used by companies to generate positive public relations is corporate social responsibility (CSR). It is critical to understand these efforts to influence the public and politicians given the risks of increased cannabis use. Objectives: To analyze cannabis industry CSR behaviors, determine their characteristics, and compare their practices with those of the tobacco industry. Design, Setting, and Participants: This qualitative study of CSR activities conducted between January 1, 2012, and December 31, 2021, evaluated 9 of the 10 largest publicly traded cannabis companies in the US and Canada. Data were collected from August 1 to December 31, 2021. The 10th company was excluded because it engaged in cannabis-based pharmaceutical sales but not CSR. A systematic review of corporate websites and Nexis Uni was performed, resulting in collection of 153 news articles, press releases, and Web pages. Charitable and philanthropic actions were included. Themes were identified and interpreted using modified grounded theory. Main Outcomes and Measures: CSR activities and spending. Results: Nine major cannabis companies in the US and Canada engaged in CSR activities that encouraged increased consumption and targeted marginalized communities. Companies claimed these activities would mitigate the harms of cannabis prohibition, promote diversity, expand access to medical cannabis, and support charitable causes. They developed educational programs, sustainability initiatives, and voluntary marketing codes and used strategies similar to those used by tobacco companies to recruit public interest organizations as allies. Conclusions and Relevance: These findings suggest that cannabis companies developed CSR strategies comparable to those used by the tobacco industry to influence regulation, suggesting that cannabis companies should be included when addressing commercial determinants of health.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".