Sexual health knowledge in a vulnerable population: a survey of adolescents in the bateyes of La Romana, Dominican Republic
Bibliographic record
Abstract
OBJECTIVE: Undocumented Haitian migrants to the Dominican Republic often live in impoverished communities called bateyes. These contexts present challenges for adolescent sexual health education. To inform development of appropriate adolescent education programs, this study assessed their general sexual health knowledge. METHODS: A locally developed sexual health knowledge survey was administered to 930 grade 7-12 adolescents attending six batey schools. Analysis of aggregated responses reviewed general demographics (e.g. age and sex), and identified top community sexual health concerns and most trusted information sources. RESULTS: Top concerns included menstruation (25.5%), HIV (21.8%), and family planning (13.3%); stratification by sex identified discordance around menstruation (89.2% female, 10.8% male) and HIV (67.1% male, 32.9% female), but not family planning (47.2% male, 52.8% female). Parents were identified as the most trusted information source, irrespective of concern. CONCLUSION: Community concerns around menstruation matches extant developing-world literature that links menarche with female stigma and school absence. Interest in HIV and family planning suggests targeted promoted efforts would be of benefit. Trust in parents is reflective of cultural traditions and suggests potential knowledge impacts arising from effective parental education.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".