Sexual and gender-related violence against girls in sub-Saharan Africa: a need for effective interventions
Bibliographic record
Abstract
High rates of sexual and gender-related violence (SGRV) against girls occur in sub-Saharan Africa. SGRV generates fear, anxiety, and depression and leads to multiple adverse outcomes; its pervasive nature constitutes a significant public health crisis; the need for effective interventions is evident as currently applied programs have known limitations, and 1 in 3 women still suffer gender-based violence in their lifetime. This report reviews the challenge and mental health impact of SGRV in sub-Saharan Africa, summarizes the strengths and weaknesses of currently applied interventions, and describes a novel social empowerment intervention piloted in Uganda which achieved nationwide reach. Girls were engaged in high schools to identify the SGRV issues they saw as priorities. A music video was recorded by celebrity artists with scenarios to illustrate these issues and promote positive interventions; this used the framework for Education-Entertainment media, a validated form of health promotion. Over 12 months, the video was viewed 36,651 times on YouTube and generated >200,000 social media posts; streaming platforms saw 113,757 individuals downloaded the song; >310,000 people at public concerts heard the song performed; and eight national broadcasters played the video or song at least 30 times reaching a combined audience of >9,500,000. We suggest these data and the inherent merit of a preventive SGRV intervention warrant further consideration of this music video model; other countries can produce region-specific, population-focused versions to meet the urgent need for targeted interventions to raise societal awareness and enhance mental health support for those living in fear of sexual violence.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".