Adolescent reports of experiencing gender based violence: findings from a cross-sectional survey from schools in a South African city
Bibliographic record
Abstract
The aim of this paper is to describe adolescent reports of gender based violence (GBV) based on a cross-sectional survey conducted with grade 8 boys and girls in high schools. . Self-completed paper based surveys were implemented with 1756 adolescents in 24 Johannesburg high schools in 2012 and with 2202 adolescents based at 30 Johannesburg high schools in 2013. Consent was required from both parents and learner in order for learners to participate. The results show high levels of GBV among adolescents, though fewer adolescents reported in 2013 than 2012. Boys were significantly more likely than girls to report experiencing all types of GBV, except for three physical GBV indicators in 2013. A specific indicator asked about rape and threats of rape. Whilst these figures were lower than asking about specific incidents of sexual violence, rates of rape were still between 8-11 %. The majority of perpetrators of rape and threats of rape were male. Adolescents were more likely to report experiences to family and friends, rather than authorities. Although a quarter of perpetrators were strangers, more were known to the victim. Findings suggest that adolescents are experiencing high levels of GBV from those known to them. Hence, there is a need for more accessible options for reporting and supporting adolescents to deal with these experiences, such as social workers in schools. Intervention and prevention strategies to deal with GBV are urgently required in the school context with both boys and girls as part of the curriculum. Keywords: Gender based violence; adolescents; reporting; school survey; help-seeking
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".