Framing coalitions and the Canadian overdose crisis: The case of opioid marketing.
Bibliographic record
Abstract
The overdose crisis remains one of the most pressing public health emergencies in North America, with the marketing of prescription opioids identified as a key contributor to its escalation. Notwithstanding, the role of prescription opioids in the current overdose crisis, as well as the extent to which marketing and education can be distinguished, remains highly debated. Using qualitative framing analysis of four separate consultations obtained through two Access to Information and Privacy (ATIP) requests, this study examines how stakeholders framed prescription opioids and the overdose crisis as policy problems, the culpability of marketing and education in the crisis, and how these framings both reflected and influenced the often-conflicting objectives of the opioid industry and public health. Findings show that while some stakeholders acknowledged problematic prescription opioid use, many reframed the crisis as an "illicit overdose crisis" and minimized the role of marketing practices. Stakeholders commonly opposed any restrictions related to prescription opioids for fear that they would bring undue attention to chronic pain patients. Overall, debates surrounding marketing and education served as proxy disagreements around safe supply, harm reduction, illicit and prescription opioids, and the appropriate role of the pharmaceutical industry in the healthcare system. Applying the analytic framework of "framing coalitions," the study highlights how stakeholders' framings and policy interests can differ and shift across overdose crisis priorities, leading to complex, overlapping constructions of the crisis. Given the crisis's varied social constructions, this research sheds light on the deep-seated tensions that fuel the deep divisions surrounding overdose crisis policies.
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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".