Evidence synthesis - The opioid crisis in Canada: a national perspective
Bibliographic record
Abstract
INTRODUCTION: This review provides a national summary of what is currently known about the Canadian opioid crisis with respect to opioid-related deaths and harms and potential risk factors as of December 2017. METHODS: We reviewed all public-facing opioid-related surveillance or epidemiological reports published by provincial and territorial ministries of health and chief coroners' or medical examiners' offices. In addition, we reviewed publications from federal partners and reports and articles published prior to December 2017. We synthesized the evidence by comparing provincial and territorial opioid-related mortality and morbidity rates with the national rates to look for regional trends. RESULTS: The opioid crisis has affected every region of the country, although some jurisdictions have been impacted more than others. As of 2016, apparent opioid-related deaths and hospitalization rates were highest in the western provinces of British Columbia and Alberta and in both Yukon and the Northwest Territories. Nationally, most apparent opioid-related deaths occurred among males; individuals between 30 and 39 years of age accounted for the greatest proportion. Current evidence suggests regional age and sex differences with respect to health outcomes, especially when synthetic opioids are involved. However, differences between data collection methods and reporting requirements may impact the interpretation and comparability of reported data. CONCLUSION: This report identifies gaps in evidence and areas for further investigation to improve our understanding of the national opioid crisis. The Public Health Agency of Canada will continue to work closely with the provinces, territories and national partners to further refine and standardize national data collection, conduct special studies and expand information-sharing to improve the evidence needed to inform public health action and prevent opioid-related deaths and harms.
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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 | 0.021 | 0.102 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.015 | 0.023 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".