UNDERSTANDING SWISS DRUG POLICY CHANGE AND THE INTRODUCTION OF HEROIN MAINTENANCE TREATMENT
Bibliographic record
Abstract
Aims: The aim of this paper is to illustrate how Switzerland was able to play such a pioneering role in the field of addiction treatment, in creating a drug policy which includes the medical prescription of diacetylmorphine (heroin).The paper will describe also the role of knowledge brokering processes and coalition building in the different phases of the development of the Swiss drug policy. DiscussionThe medical prescription of diacetylmorphine was the exotic element of the new Swiss drug policy of 1991 and still is probably one of the most controversial practices in clinical medicine despite its documented effectiveness.Coalitions of change actors, across stakeholder groups from many professions and politicians on various levels, succeeded in formulating and starting initiatives for a new drug policy and its innovations.Clear shared objectives, and a common feeling of urgency brought the coalitions together.Knowledge brokering processes enhanced the use of research in policy formulation by organizing existing and new interactions between researchers and policy makers. ConclusionIn the case of Switzerland, the Confederation took a leading role by facilitating communication, encouraging scientific knowledge and bringing the various stake-holders on a platform to deliver a consensual political policymaking basis.This was facilitated by the Swiss direct democracy system.Sustained dialogue between researchers and the users of research enhances the likelihood of research affecting policy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".