“An Adventure That Went Wrong”: Reasons Given by Convicted Perpetrators of Multiple Perpetrator Sexual Offending for Their Involvement in the Offense
Bibliographic record
Abstract
There is little empirical research examining the reasons behind multiple perpetrator sexual offending. A limited number of studies provide reasons for offending offered by perpetrators of this type of sexual violence, but only one published study exists where these perpetrators were interviewed regarding their offense. The Multi-Factorial Model of Multiple Perpetrator Sexual Offending (MPSO) proposed that various factors (individual, sociocultural, and situational) play a role in this type of sexual assault, noting in particular the importance of group dynamics and processes. In the current study, 25 convicted perpetrators of multiple perpetrator sexual offending housed in educational centers and prisons in Portugal were interviewed about their involvement and reasons for participating in the offense. The findings suggested that group processes and dynamics play an important part in this type of sexual offending. Furthermore, the results provided some evidence to support the factors proposed by the Multi-Factorial Model of MPSO. These findings have implications for prevention and treatment programs and for the assessment of offenders.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".