Assessing the future of maintenance treatment in Canada in an international context: an analysis of current initiatives and historical practices - 1900 to 2010
Bibliographic record
Abstract
The treatment of addiction poses a significant challenge. This challenge is a result of the complexity of addiction itself as a health problem and because a full understanding of what causes addiction is something that still eludes researchers and clinicians. Add to this situation the reality that addiction is an issue with significant political, social and legal dimensions and its treatment becomes complicated. This complexity evokes questions about why different forms of treatment are advanced, accepted or rejected. This dissertation provides insight into this through an examination of heroin maintenance. The dissertation is a study of the history of heroin maintenance, including present-day developments, across a number of nations. Its purpose is to identify a set of forces that can explain recent experimentation with heroin maintenance and offer insight into its sustainability in Canada. Six countries are included: Canada, the US, the UK, the Netherlands, Germany and Switzerland. A mixed method, qualitative approach is employed and relies on three data sources: 1) health and sociology-oriented literature, 2) archival data from government departments and addiction treatment agencies, and 3) interviews with heroin maintenance trial stakeholders. Using the work of David Garland and the critical literature on harm reduction as a theoretical framework, a number of social and political forces have been identified as essential to the implementation of heroin maintenance. These include: 1) models of drug control, 2) perspectives on addiction and its treatment, 3) drug-related crises/epidemics, 4) pragmatism and evidence, 5) how heroin maintenance is framed, 6) local support and action, 7) political environments, 8) international developments/ pressures, and 9) the extent of medical ownership of addiction, professional influence and expert advocacy. These forces all interact to produce conditions that are either favourable for introducing heroin maintenance or inhibit its use. An analysis of the current Canadian context based on these factors suggests that the sustainability of heroin maintenance is questionable. A drug policy environment increasingly guided by social conservativism and declining political, public and professional attention to heroin addiction may impede moving such a controversial and expensive service from a research setting to a routine treatment option in Canada.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".