Short and long-term prediction of recidivism using the youth level of service/case management inventory in a sample of serious young offenders.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present investigation examined the predictive accuracy of the Youth Level of Service/Case Management Inventory (YLS/CMI) for youth and adult recidivism in a Canadian sample of 167 youths (93 males, 74 females) charged with serious offenses who received psychological services from a community mental health outpatient clinic. Youths were followed for an average of 7 years in the community, and predictive accuracy was examined for several recidivism outcomes as a function of gender, ethnicity, and developmental age group. YLS/CMI total scores significantly predicted all recidivism categories in the overall sample (area under the curve values ranged from 0.66 to 0.77) although the instrument as a whole, and its criminogenic needs, demonstrated somewhat stronger and more consistent predictive accuracy for youth outcomes. The YLS/CMI also demonstrated significant predictive accuracy within demographic subgroups. The implications of these findings are discussed in terms of the use of risk-need assessment tools in providing clinical assessment, treatment, and case management services to diverse young offender groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it