The influence of social and environmental factors on drug use in female prisoners
Bibliographic record
Abstract
Limited quantitative evidence exists for the potential impact of social and environmental factors on drug use during imprisonment. Self-report data were collected from 211 adult women (88% response rate) in Belgian prisons, representing 42% of all female prisoners nationwide. During their current incarceration, one in three (31%) participants had ever used drugs and a quarter (26%) did so in the past month. Cannabis and non-prescribed tranquillizers (such as benzodiazepines) were most commonly used. The main reasons cited by participants for using drugs in prison were to relieve stress, forget problems, and counteract boredom. In a multivariate analysis, perceived social support and availability of meaningful activities were negatively associated with recent drug use while incarcerated. Other factors related to the prison environment had no significant influence on drug use, providing a more nuanced perspective on extant qualitative literature.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".