The opioid crisis in canada – Governmental responses and strategies
Bibliographic record
Abstract
The opioid crisis in canada – Governmental responses and strategies Norm Buckley, Scientific Director at the Michael G. DeGroote Institute for Pain Research & Care, and Jason Busse, Director of the Michael G DeGroote National Pain Centre at McMaster University, discuss the complexities of chronic pain management and addressing the opioid crisis. The National Advisory Council on Prescription Drug Misuse was formed to address the opioid crisis in Canada. Led by the Canadian Centre on Substance Abuse (now known as the Canadian Centre on Substance Abuse and Addiction), the Coalition on Prescription Drug Misuse (Alberta), and the Nova Scotia Department of Health and Wellness, in partnership with Health Canada’s First Nations and Inuit Health Branch’s Prescription Drug Abuse Coordinating Committee (PDACC), the Council released First Do No Harm: Responding to Canada’s Prescription Drug Crisis in March 2013. Half of the recommendations addressed issues regarding chronic pain, recognizing the link between opioid prescribing and chronic pain. The Council recommended establishing competencies for healthcare professionals, improving healthcare professional curricula for pain and addiction, ensuring access to optimal care for pain as well as addiction, and supporting research that would optimize evidence-based care of patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.035 | 0.016 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.009 | 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".