ral Substance Abuse Treatment, ssBioMed CentPrevention, and Policy
Bibliographic record
Abstract
Background: Street-involved youth are a population at risk of adopting injection as a route of administration, and preventing the transition to injection drug use among street youth represents a public health priority. In order to inform epidemiological research and prevention efforts, we conducted a qualitative study to investigate the initiation of injection drug use among street-involved youth in Vancouver, Canada. Methods: Qualitative interviews with street youth who inject drugs elicited descriptions of the adoption of injection as a route of administration. Interviewees were recruited from the At-Risk Youth Study (ARYS), a cohort of street-involved youth who use illicit drugs in Vancouver, Canada. Audio recorded interviews were transcribed verbatim and a thematic analysis was conducted. Results: 26 youth aged 16 to 26 participated in this study, including 12 females. Among study participants the first injection episode frequently featured another drug user who facilitated the initiation of injecting. Youth narratives indicate that the transition into injecting is influenced by social interactions with drug using peers and evolving perceptions of injecting, and rejecting identification as an injector was important among youth who did not continue to inject. It appears
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 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; 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".