Child sexual abuse in youth-oriented organisations: tapping into situational crime prevention from the offender’s perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
How to prevent child sexual abuse in youth-oriented organisations is a concern in our society for a number of reasons. One of these is that evidence indicates that sexual offenders, once they are recruited by a youth-oriented organisation, have the opportunity to abuse children for years before being detected and/or arrested. This phenomenon is also under intense media scrutiny, which is likely to lead parents and society in a direction of panic. In the tradition of offender-based research, and using a sample of 23 Canadian adult sex offenders who offended in a youth-oriented organisation (e.g., schools), we examined self-reported data from a situational crime prevention perspective. We specifically focused on information provided by offenders on three dimensions: (1) how to identify potential offenders during recruitment interviews; (2) what policies or regulations to implement in youth-oriented organisations to prevent child sexual abuse; and, (3) what parents could do to reduce the risk of sexual victimisation of their children. Then, the 25 situational prevention measures table is adopted to provide an organisational framework to map out suggestions made by offenders to inform prevention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it