A Call for Social Work Intervention to Address the Phenomenon of Child Sexual Abuse against Learners in South African Schools: A Review of the Literature
Bibliographic record
Abstract
Child sexual abuse (CSA) is undoubtedly one of the social problems negatively affecting children in South Africa. Everyday reports in research and different media platforms such as radio, television, social media and newspapers suggest that sexual abuse of children and those attending school, has reached unprecedented proportions. Within the school setting, it is reported that school-based employees such as teachers, security personel and gardeners are alleged to be the perpetrators of this heinous crime against children. The purpose of this paper through the literature review methodology, is to highlight the phenomenon of CSA perpetrated against learners in the South African schools and indicate how the social work profession may intervene. To this end, this paper calls social workers to intervene by means of educating learners on child sexual abuse, establishing and strengthening the childcare and protection forums, engaging parents, guardians and lastly facilitating dialogues with the school-based employees. These interventions will go a long way in addressing the phenomenon of CSA, and most importantly, protecting the rights of children as the most vulnerable group in societies.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".