Vulnerability of Nigerian secondary school to human sex trafficking in Nigeria.
Bibliographic record
Abstract
Sex trafficking contributes to the cycle of violence against women, and inflicts global social and health consequences, particularly in this era of HIV/AIDS pandemic. This paper is based on a cross-sectional survey conducted in two urban and two rural schools located in Delta and Edo states of Nigeria. The aim is to assess in-school students' knowledge and awareness of, and attitude toward sex trafficking as a way to understanding their personal vulnerability to trafficking. A semi-structured questionnaire was administered in 2004-2005 to a classroom random sample of 689 adolescents in the age range of 16-20 years. The results show that in-school adolescents are vulnerable to sex trafficking due to poverty (77.2%); unemployment (68.4%); illiteracy (56.1%); and low social status (44.5%). Students in co-ed schools showed higher knowledge and awareness of the serious health consequences of trafficking.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".