The importance of social networks in their association to drug equipment sharing among injection drug users: a review
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
AIM: To examine the scientific evidence regarding the association between characteristics of social networks of injection drug users (IDUs) and the sharing of drug injection equipment. METHODS: A search was performed on MEDLINE, EMBASE, BIOSIS, Current Contents, PsycINFO databases and other sources to identify published studies on social networks of IDUs. Papers were selected based on their examination of social network factors in relation to the sharing of syringes and drug preparation equipment (e.g. containers, filters, water). Additional relevant papers were found from the reference list of identified articles. RESULTS: Network correlates of drug equipment sharing are multi-factorial and include structural factors (network size, density, position, turnover), compositional factors (network member characteristics, role and quality of relationships with members) and behavioural factors (injecting norms, patterns of drug use, severity of drug addiction). Factors appear to be related differentially to equipment sharing. CONCLUSIONS: Social network characteristics are associated with drug injection risk behaviours and should be considered alongside personal risk behaviours in prevention programmes. Recommendations for future research into the social networks of IDUs are proposed.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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