Characteristics of young illicit drug injectors who use North America's first medically supervised safer injecting facility
Bibliographic record
Abstract
The study examined whether North America's first medically supervised safer injection facility (SIF) attracts young injection drug users (IDUs) who are at high risk of health-related harm. Prevalence of SIF use was determined based on data obtained after the SIF's opening. Predictors of initiating future SIF use were determined based on behavioral information obtained from the participant's study visit immediately preceding the SIF's opening. The median duration between the acquisition of pre-SIF opening behavioral data and the more recent interview, where SIF use was measured, was 16 months. Characteristics of IDUs who did and did not subsequently initiate SIF use were statistically compared (N = 135). Data from the 6-month period prior to the SIF's opening showed that youth initiating SIF use were significantly more likely to have been in jail, to use heroin daily, to have overdosed, to have binged on drugs, to have loaned needles, and to have been homeless. The study suggests that among IDUs 29 years of age or younger, those who used the SIF were at higher risk than those who were not.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".