Pilot Implementation and Preliminary Evaluation of START:AV Assessments in Secure Juvenile Correctional Facilities
Bibliographic record
Abstract
The Short-Term Assessment of Risk and Treatability: Adolescent Version (START:AV) is a new structured professional judgment guide for assessing short-term risks in adolescents. The scheme may be distinguished from other youth risk assessment and treatment planning instruments by its inclusion of 23 dynamic factors that are each rated for both vulnerability and strength. In addition, START:AV is also unique in that it focuses on multiple adverse outcomes-namely, violence, self-harm, suicide, unauthorized leave, substance abuse, self-neglect, victimization, and general offending-over the short-term (i.e., weeks to months) rather than long-term (i.e., years). This paper describes a pilot implementation and preliminary evaluation of START:AV in three secure juvenile correctional facilities in the southern United States. Specifically, we examined the descriptive characteristics and psychometric properties of START:AV assessments completed by 21 case managers on 291 adolescent offenders (250 boys and 41 girls) at the time of admission. Results provide preliminary support for the feasibility of completing START:AV assessments as part of routine practice. Findings also highlight differences in the characteristics of START:AV assessments for boys and girls and differential associations between the eight START:AV risk domains. Though results are promising, further research is needed to establish the reliability and validity of START:AV assessments completed in the field.
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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 | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".