Ambivalence about supervised injection facilities among community stakeholders
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Community stakeholders express a range of opinions about supervised injection facilities (SIFs). We sought to identify reasons for ambivalence about SIFs amongst community stakeholders in two Canadian cities. FINDINGS: We used purposive sampling methods to recruit various stakeholder representatives (n = 141) for key informant interviews or focus group discussions. Data were analyzed using a thematic process. We identified seven reasons for ambivalence about SIFs: lack of personal knowledge of evidence about SIFs; concern that SIF goals are too narrow and the need for a comprehensive response to drug use; uncertainty that the community drug problem is large enough to warrant a SIF(s); the need to know more about the "right" places to locate a SIF(s) to avoid damaging communities or businesses; worry that a SIF(s) will renew problems that existed prior to gentrification; concern that resources for drug use prevention and treatment efforts will be diverted to pay for a SIF(s); and concern that SIF implementation must include evaluation, community consultation, and an explicit commitment to discontinue a SIF(s) in the event of adverse outcomes. CONCLUSIONS: Stakeholders desire evidence about potential SIF impacts relevant to local contexts and that addresses perceived potential harms. Stakeholders would also like to see SIFs situated within a comprehensive response to drug use. Future research should determine the relative importance of these concerns and optimal approaches to address them to help guide decision-making about SIFs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it