Supervised consumption sites' variability outlined
Bibliographic record
Abstract
An article on supervised consumption sites found that there are no strict rules for how they operate, and that they are “as varied as the communities in which they operate.” The article, published in the April 6 issue of the Journal of the American Medical Association ( JAMA ), quoted Kimberly Sue, M.D., Ph.D., medical director of the National Harm Reduction Coalition, on the fact that “These are things that people who use drugs and people who care about them have been doing for years.” The sites can be as simple as a social service agency restroom stall, or as expansive as Vancouver's Insite, which has hundreds of injection room visits a day and offers detox rooms with private bathrooms, transitional housing and other wraparound services. Because the main cause of opioid overdose deaths is respiratory depression, naloxone is essential. So is sternal pressure to stimulate breathing, the article noted. Most supervised consumption sites aim to prevent HIV transmission, wound infection and help for people who inject drugs in general. “People wrongly assume that people using drugs don't care about their health,” Alex Kral, Ph.D., an epidemiologist with the nonprofit research institute RTI International in Berkeley, California, told JAMA . Jim McDonald, M.D., M.P.H., interim director of the Rhode Island Department of Health, said supervised consumption sites shouldn't operate underground, the way Kral's does. “Let's recognize they need a safe place to use,” McDonald, who oversees the state's overdose prevention efforts, said in an interview. Substance use disorder “is a complex biopsychosocial problem,” he noted, “but it doesn't get better by keeping secrets.” The federal Department of Justice knows what Rhode Island is doing, said McDonald. Rhode Island's first harm‐reduction centers, part of a two‐year pilot program, were hoped to open soon. One problem is NIMBY — the “not in my backyard” issue presented by communities that support supervised consumption sites — somewhere else. Kral's work is supported in part by Arnold Ventures, the article, “Supervised Consumption Sites — A Tool for Reducing Risk of Overdose Deaths and Infectious Diseases in People Who Use Illicit Drugs” by Rita Rubin and colleagues, disclosed.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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; both teacher heads agree on what is shown here.
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".