Bibliographic record
Abstract
Harm reduction practices have been identified as effective and promising approaches to drug use. Instead of focusing on drug users giving up using drugs, the principles of harm reduction aim to reduce the harms associated with drug addiction (Ontario Harm Reduction Distribution Program, n.d.). Providing clean needles and syringes without a limit on the amount, harm reduction practices encourage drug users to access the supplies needed to ensure they are injecting drugs safely and prevent the spread of blood-borne diseases (Ontario Harm Reduction Distribution Program, n.d.).\nIn response to the increasing incidences of intravenous drug use and disease transmission, the Counterpoint needle exchange program began in London, Ontario in 1992. In collaboration with the Regional HIV/AIDS Connection, the Middlesex-London Health Unit has operated the needle exchange service through the sexual health clinic (Regional HIV/AIDS Connection, n.d.). In 2008, fully supported by the City of London through the London Homeless Prevention System, London CAReS was established, and one of its roles was to keep public areas free of discarded needles (Regional HIV/AIDS Connection, n.d.).\nIn 2014, a six-year-old boy got a needle stick injury in a public toilet. This accident immediately created public panic, engendering a public discussion on how to manage needles safely and educating needle users on safe needle disposal. To improve the needle exchange program in London, it is important to understand project details and review the landscape of community programs, policies, and activities related to needle/syringe disposal. By comparing different programs, similarities and differences will be identified.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".