The Relationship Between Matching Service to Criminogenic Need and Recidivism in Male and Female Youth
Bibliographic record
Abstract
Research supports rehabilitative programming that recognizes youth’s level of risk to reoffend and addresses their criminogenic needs and responsivity factors. The risk–need–responsivity (RNR) framework takes a gender-neutral approach that critics assert overlooks the unique needs of female offenders. While matching treatments to RNR principles has been shown to reduce recidivism for male youth, it is unclear whether the same is true for female youth. Comparative analyses of 39 male and 37 female justice system–involved youth indicated that across RNR categories, females and males were similar in the quality and quantity of criminogenic needs and had these needs met through probation services at a similar rate. However, while the RNR assessment tool predicted recidivism equally well for male and female youth, the matching of services to RNR factors was significantly associated with reduced reoffending for boys but not for girls. Implications of the findings for theory and practice are discussed.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".