Trends and sex differences in prescription opioid deaths in British Columbia, Canada
Bibliographic record
Abstract
Increasing rates of prescription opioid-related death are well documented in Ontario (ON) but little is known about prescription opioid-related harms in other Canadian provinces. Using administrative mortality data from 2004 to 2013, we found that rates of prescription opioid-related death in British Columbia (BC) were higher but more stable than published rates for ON over the same period. Methadone was involved in approximately 25% of the prescription opioid-related deaths in BC. The majority of prescription opioid-related deaths among men and women were unintentional. Men had higher overall rates of prescription opioid-related deaths in BC; women had lower rates of prescription opioid-related deaths but a larger proportion of them were suicides. Efforts to reduce prescription opioid-related deaths must consider sex differences in patterns of prescription opioid use and associated harms.
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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".