Unanticipated Changes in Drug Overdose Death Rates in Canada During the Opioid Crisis
Bibliographic record
Abstract
Escalating drug overdose death rates in Canada are of ever-increasing concern. To better understand the extent of this health threat, we obtained mortality statistics and population figures for the years 2000 to 2020, and examined rates of overdose deaths, coded (using ICD-10) as accidental, suicide or "undetermined intent." The drug deemed as primarily responsible for the death was categorized as opioid, non-opioid, or unspecified. Age patterns of drug deaths were graphed. Joinpoint analysis was used to test the significance of changes in death rates. Accidental opioid and stimulant overdose death rates in Canada have climbed faster since 2011, though not as high as corresponding US rates. Unknown cause death rates have increased. However, opioid and non-opioid suicide rates have decreased significantly since 2011, and there have been fewer drug deaths of undetermined intent. Increased attention to the possibility that some suicides are being misclassified is warranted.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".