Raising Awareness of Sexual Abuse among Children with Intellectual Disabilities: A Survey of Teachers' Views
Bibliographic record
Abstract
Sexual abuse is one of the most dangerous phenomena that can overwhelm any society. Children with ID seem to be among the groups with the highest risks for sexual abuse/maltreatment. This research aims to investigate teachers' views regarding how raising awareness of sexual abuse among children with intellectual disabilities. This phenomenon is not spared even the mentally handicapped, as they may not realize the extent of the abuse they are exposed to and may not tell anyone about it, because they do not understand it, they may not realize the standards of religion, society, and standards of social behavior. The sample was 40 teachers of children with intellectual disabilities from Madina El Monawara. This study utilized a qualitative research technique. To collect data, a semi-structured interview method was employed. In response to some big questions: What causes for high prevalence rates of sexual abuse in individuals with ID? How to raise children with intellectual disabilities' awareness of Sexual Abuse? According to teachers' views, lack of social skills, lack of sexual knowledge, inequality in relationships, and the fact that in some cases, individuals with ID need to depend on others were the main causes. Educating children with ID to say no to bad touches, getting to report being victims of sexual abuse, getting them to understand what sexual abuse is or that sexual abuse is a crime, not to be afraid of repercussions they may face from their abuser, or feel ashamed, embarrassed, or blame themselves for the abuse are the most frequently reported recommendations to raise children with intellectual disabilities' awareness of Sexual Abuse.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".