Bibliographic record
Abstract
Providing supervised access to pharmaceutical heroin to people whose use continues after trying multiple traditional treatments has been successful in other countries and should be piloted and studied in the United States, according to a RAND Corporation study released Dec. 6. “Given the increasing number of deaths associated with fentanyl and successful use of heroin‐assisted treatment abroad, the U.S. should pilot and study this approach in some cities,” said Beau Kilmer, leader of the project and co‐director of the RAND Drug Policy Research Center. “This is not a silver bullet or first‐line treatment. But there is evidence that it helps stabilize the lives of some people who use heroin.” The RAND findings appear in five related RAND publications and are based on experiences in other countries, including Canada, where Vancouver has that country's only heroin prescription. To assess the effectiveness of heroin‐assisted treatment and supervised consumption sites, RAND researchers reviewed scientific evidence and talked to more than two dozen stakeholders in Canada, the Netherlands, Switzerland and the United Kingdom to learn about their experiences with the approaches. They also spoke to more than 150 people in New Hampshire and Ohio, two states hard hit by opioid overdoses. The researchers found the documentation supporting supervised injection sites to be less solid than that supporting medical‐grade heroin provision. “Persistence does not imply effectiveness, but it seems unlikely that supervised consumption sites — which were initially controversial in many places — would have such longevity if they had serious adverse consequences for their clients or communities,” Kilmer said. For example, supervised consumption sites currently supervise a very small proportion of all injection sessions even in cities where they are well‐established. “It may even be worth asking whether the benefits of supervised consumption sites depend on there being a physical brick‐and‐mortar site, which may become a lightning rod for opposition, or if the key is just that consumption is supervised and whether there are other ways to get more opioid consumption supervised,” said Jonathan P. Caulkins, a report co‐author and a professor of public policy at Carnegie Mellon University. Caulkins said it also is possible that supervised injection of hydromorphone — a prescription opioid medication — may achieve similar benefits as offering supervised injectable heroin for those with heroin use disorder, but with fewer regulatory barriers in the United States, where heroin is illegal. The report, Considering Heroin‐Assisted Treatment and Supervised Drug Consumption Sites in the United States , is available at www.rand.org . Funding for the study was provided by RAND Ventures, which is supported by gifts from RAND supporters and income from operations.
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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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 0.004 |
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".