National Health Insurance and Health-Based Drug Policy: An Examination of Policy Linkages in the USA and Canada
Bibliographic record
Abstract
For more than 50 years the United States and Canada maintained illegal-drug policies that followed the same course: a long period of punitive prohibition followed by moderation and an emphasis on drug abuse as a public health problem. Then in the 1980s, the USA reverted to a punitive model while Canada increased its commitment to a health-based approach. Why this divergence after following the same path for so long? In this paper I argue that one factor was Canada's adoption of national health insurance, which guaranteed universal access to health care, including addiction treatment. As the country's most popular policy it was protected against budget cuts during a period of welfare-state retrenchment in the 1980s. In the USA, on the other hand, public health insurance was limited to the elderly and the poor, and addiction treatment services were isolated and stigmatized. Thus the public health side of drug policy was poorly positioned to resist welfare cutbacks and ascendant criminal-justice interests. The experiences of the USA and Canada have implications for policy reformers and for the study of how institutional interests cross policy domains.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.017 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".