Examining Benchmarks of Sexual Recidivism Rates for Short, Moderate, and Long-Term Follow-Up Periods: A Meta-Analysis of Canadian and American Studies
Bibliographic record
Abstract
Measuring sexual recidivism involves both a behavioral and a temporal component. The behavioral component is sexually reoffending, generally measured using official sources. The temporal component is the follow-up period during which sexual recidivism is examined. Research has shown that if the length of the follow-up period is extended, rates of sexual recidivism increase. What is less clear is the functional form of this relationship. The present study examines this relationship through a meta-analysis of 468 sexual recidivism studies conducted in Canada and the United States and published since 1940. The weighted pooled mean recidivism rates ranged from 0.06 (95% CI [0.05, 0.09]; mean follow-up of less than 3 years) to 0.17 ([0.12, 0.23]; mean follow-up of 12 years or more). These benchmarks should be used with caution given the wide variability of recidivism rates observed in studies with similar mean follow-up periods. Such caution is especially needed in when communicating the risk of recidivism over longer-term follow-up periods given the limited number of such studies.
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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 | 0.072 | 0.126 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.058 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".