Child Sexual Abuse, Disclosure and Reintegration: Too Late or Too Soon.
Bibliographic record
Abstract
There is a lot of news reporting in Nigeria on the sexual abuse of children, especially the female child. Several of these abuses occur during domestic work or in children’s family homes with perpetrators who could be close family members (parents, siblings or distant relatives), friends, neighbours, teachers or strangers. Bearing in mind that child sexual abuse is a social issue that could benefit from a more nuanced understanding of the problem, children facing sexual abuse are better positioned to provide critical insight into their diverse experiences and triggers of the problem. It is essential to speak to affected children to understand factors reinforcing their abuse and the nature of resources available and desired by them for effective reintegration or adjustment after exiting protection offered by anti-trafficking shelters. The paper interacts with African Centred approaches as studies indicate that the peculiarities of the African culture manifested in Ubuntu, have a significant effect on the incidence and disclosure rates of child sexual abuse in Africa, the recently instituted Nigeria Sex Offender’s Registry, and children’s diverse narratives for a critical discussion on the problem. Several themes generated from the findings highlight the link between child labour and child susceptibility to sexual abuse. The findings also indicate the trauma of disbelief, stigma, culture of silence or lack of disclosure surrounding and reinforcing children’s encounter with sexual exploitation. These narratives limit the nature of children’s reintegration with families after disclosure of sexual experiences and should shape the direction of interactions for addressing children’s problems.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| 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".