The role of prisons in the HIV epidemic among female injecting drug users
Bibliographic record
Abstract
The objective of this study was to describe factors associated with imprisonment of female injecting drug users (IDUs) and to assess if female IDUs who have been in prison have different HIV risk behaviours when compared to females IDUs who have never been incarcerated. A seroepidemiological survey was conducted of 304 female IDUs recruited in outreach and treatment programmes in Madrid, Spain. Data on sociodemographic characteristics and recent and lifetime risk factors, sexual and reproductive history and history of imprisonment were collected. Bivariate analysis and a logistic regression model were used to identify factors associated with imprisonment. Risk factors for imprisonment were having illegal sources of income, not having a fixed address, leaving education before finishing primary school and starting injection of drugs early in adolescence. HIV risk behaviours were highly prevalent among this population of female IDUs and drug injection in prison was reported by more than one-third of those who had ever been imprisoned. In addition, recent HIV risk behaviour indicators were not associated with imprisonment, suggesting that incarceration did not lead to risk reduction after release from prison. Female IDUs who have been in prison have substantial reproductive health problems that require gynaecological care. These results point to the urgent need for prevention programmes which address HIV and other blood-borne infections using gender specific approaches for women IDUs incarcerated in Spanish prisons.
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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 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".