The risk-related correlates & recidivism of victim age polymorphism : a meta-analysis
Bibliographic record
Abstract
Victim age polymorphism refers to individuals who sexually offend against victims in multiple age categories (e.g., both child and adult victims).Despite some findings that this group tends to be higher risk of recidivism than non-age polymorphic groups, the literature on victim age polymorphism and its association with risk-related correlates and recidivism is mixed.The present study used meta-analyses to examine the associations between victim age polymorphism and the two main risk-related correlates (atypical sexual interests, antisociality) and recidivism.Database searches retrieved 2,924 articles, resulting in the inclusion of 22 studies.Results revealed that victim age polymorphism was associated with the antisociality risk domain and violent recidivism.A small positive association with atypical sexual interests and sexual recidivism also emerged.Overall, individuals with offences that are victim age polymorphic appeared to share more clinically relevant similarities to individuals who target exclusively adults than to individuals who exclusively target children.August 16, 2023 analyses.This project greatly benefitted from the time & effort they generously donated.I would also like to thank several other individuals who provided additional support in the form of author contact information, clarifications on methodology, sample criteria, and/or kind words: Drs.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.031 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".