Profiles of SAVRY risk and protective factors within male and female juvenile offenders: A latent class and latent transition analysis
Bibliographic record
Abstract
This longitudinal study explored the existence of, and the transition between, latent classes based on risk/need domains of the Structured Assessment of Violence Risk in Youth (SAVRY). The study included 4,267 male and 661 female justice-involved juveniles who had at least one SAVRY assessment completed between 2006 and 2011. A three-step approach was used for the latent class analyses (LCA): (1) A standard LCA estimated the classes; (2) the class-membership was determined; and (3) latent transition analyses estimated the likelihood of transition between the subgroups. For male adolescents, five latent classes were identified: (a) low risk/needs (36%); (b) low-moderate risk/needs (26%); (c) moderate risk/needs (11%); (d) moderate-high risk/needs (19%); and (e) high risk/needs (8%). For female adolescents, three subgroups were identified: (a) low risk/needs (30%); (b) moderate risk/needs (51%); and (c) high risk/needs (19%). Recidivism rates differentiated the subgroups, and the likelihood of transition within a 12-months timeframe was low.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".