Exploring Contextual and Individual Factors Influencing Prevalence of Sexual Assault among Female Young People in Anambra State, Nigeria
Bibliographic record
Abstract
Sexual assault poses a global threat, impacting victims, families, and societies both in short-term and long-term. This study aims to understand the contextual and individual factors contributing to the high prevalence of sexual assault among young females (aged 10 to 24) in Anambra State, Nigeria. Conducted as a descriptive qualitative study, data were gathered from thirty-one participants, including twenty-three stakeholders and eight rape victims, through two focus group discussions (FGDs) and thirteen in-depth interviews (IDIs). Recorded data was transcribed verbatim and analyzed thematically using NVivo 12. The study identified eight major contextual factors influencing sexual assault: socioeconomic status, drug abuse, level of morality, policy implementation, insecurity, and unemployment. Significant individual factors include the occupation of young people, parenting style, dressing choices, educational institution affiliation, individual conduct, and indiscriminate use of electronic devices. The study concludes that policies aimed at revitalizing moral instruction in schools, curbing drug use, addressing indecent dressing, and regulating phone use among young people are crucial in controlling sexual assault.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".