The Kids Are All White: Examining Race and Representation in News Media Coverage of Opioid Overdose Deaths in Canada
Bibliographic record
Abstract
Problematic opioid use in Canada is on the rise, and opioid overdose deaths now number in the thousands each year. While opioids have long been responsible for overdoses among certain demographics of Canadians, such as drug users on Vancouver's notoriously impoverished downtown Eastside, it is only recently that fatal overdoses have also claimed the lives of White, middle‐class young people. This critical discourse analysis of Canadian news media examines the differences in racial representation in recent coverage of opioid deaths. I pay particular attention to the ways in which White opioid users are portrayed as innocent victims while other users, such as those from Indigenous communities, are often ignored or stigmatized as “addicts.” I draw on the work of Hall (1978; 2000) and Reinarman and Levine (1989; 2004) on the role of media in representing race and constructing drug scares, to frame the media narratives. I then discuss the Canadian government's current harm‐reduction approach to the opioid crisis, as well as calls from Indigenous leaders for “culture as treatment.”
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".