Original Contribution Gang Exposure and Pregnancy Incidence among Female Adolescents in San Francisco: Evidence for the Need to Integrate Reproductive Health with Violence Prevention Efforts
Bibliographic record
Abstract
Among a cohort of 237 sexually active females aged 14–19 years recruited from community venues in a pre-dominantly Latino neighborhood in San Francisco, California, the authors examined the relation between gang exposure and pregnancy incidence over 2 years of follow-up between 2001 and 2004. Using discrete-time survival analysis, they investigated whether gang membership by individuals and partners was associated with pregnancy incidence and determined whether partnership characteristics, contraceptive behaviors, and pregnancy intentions mediated the relation between gang membership and pregnancy. Pregnancy incidence was determined by urine-based testing and self-report. Latinas represented 77 % of participants, with one in five born outside the United States. One quarter (27.4%) became pregnant over follow-up. Participants ’ gang membership had no significant effect on pregnancy incidence (hazard ratio 1.25, 95 % confidence interval: 0.54, 3.45); however, having partners who were in gangs was associated with pregnancy (hazard ratio 1.90, 95 % confidence interval: 1.09, 3.32). The male partner’s perceived pregnancy intentions and having a partner in detention each mediated the effect of partner’s gang membership on pregnancy risk. Increased pregnancy incidence among young women with gang-involved partners highlights the importance of integrating reproductive health prevention into programs for gang-involved youth. In addition, high pregnancy rates indicate a heightened risk for sexually transmitted infections.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".