Correctional Intake Assessment and Case Planning: Application Development and Validation
Bibliographic record
Abstract
The Intake Assessment (IA) process in the Canadian federal correctional system results in an individualized treatment and supervision plan throughout the sentence. Two components, Static and Dynamic Factors Assessment, were examined to determine whether a streamlined version could be tailored for a hand-held mobile application and remain reliable and valid for correctional planning purposes. An Information Management System database was used to identify all first releases from federal custody over a 2-year period who had IA data available ( N = 6,946). Analyses revealed statistically significant relationships and AUCs (area under receiver operating characteristic curves) for both the Static and Dynamic Factors components of IA with respect to reincarceration. Additional analyses revealed that the strongest predictors for returns to federal custody were criminal history as a youth or adult, substance misuse, and unemployment. A combined Static and Dynamic Factors score also yielded a simplified, robust, and incremental predictor of reincarceration for both men and women.
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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 | 0.000 | 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 | 0.001 | 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".