Contact Sexual Offending by Men With Online Sexual Offenses
Bibliographic record
Abstract
There is much concern about the likelihood that online sexual offenders (particularly online child pornography offenders) have either committed or will commit offline sexual offenses involving contact with a victim. This study addresses this question in two meta-analyses: the first examined the contact sexual offense histories of online offenders, whereas the second examined the recidivism rates from follow-up studies of online offenders. The first meta-analysis found that approximately 1 in 8 online offenders (12%) have an officially known contact sexual offense history at the time of their index offense (k = 21, N = 4,464). Approximately one in two (55%) online offenders admitted to a contact sexual offense in the six studies that had self-report data (N = 523). The second meta-analysis revealed that 4.6% of online offenders committed a new sexual offense of some kind during a 1.5- to 6-year follow-up (k = 9, N = 2,630); 2.0% committed a contact sexual offense and 3.4% committed a new child pornography offense. The results of these two quantitative reviews suggest that there may be a distinct subgroup of online-only offenders who pose relatively low risk of committing contact sexual offenses in the future.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".