‘If my parents find out, I will not see my phone anymore’: Who do children choose to disclose online sexual solicitation to?
Bibliographic record
Abstract
Abstract Child online sexual solicitation has become a significant form of child sexual abuse. Disclosure of online sexual solicitation is a multifaceted and complex process. The role of the disclosure recipient is crucial in the disclosure process, with respect to the initiation of the disclosure, how much children disclose, recantations and the children's well‐being. The current study aimed to explore children's experiences, perceptions, challenges and obstacles regarding disclosing online sexual solicitation as revealed in their forensic interviews. The sample, obtained from the Service of Forensic Interviews with Children in Israel, included 32 Israeli children who were sexually solicited online and participated in forensic interviews. A thematic qualitative methodology was used to analyse the children's narratives. The findings demonstrated that children tend to disclose online sexual solicitation to their peers and not to their parents. The children provided three main reasons for this tendency: sexuality, technology and the recipient's response. The current study's findings highlight the important role of peers in the disclosure process of online sexual solicitation. Moreover, the findings reveal children's difficulties disclosing online sexual solicitation to their parents. Practical implications of children's online sexual solicitation disclosure, future recommendations and study limitations are discussed.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".