Costs of Criminal Justice Involvement Among Persons With Serious Mental Illness in Connecticut
Bibliographic record
Abstract
OBJECTIVE: This study sought to describe patterns and costs of criminal justice involvement among adults with serious mental illness who received services across public agencies within a single state. Costs were examined from the perspective of state agencies providing mental health, substance abuse, and criminal justice services. METHODS: Administrative records for 25,133 adults who were served by the Connecticut Department of Mental Health and Addiction Services (DMHAS) during fiscal years 2006 and 2007 and who had a diagnosis of schizophrenia or bipolar disorder were matched with records of the state Medicaid program, Judicial Branch, Department of Correction, and Department of Public Safety. Unit costs for service events were combined with utilization data to calculate costs per person. RESULTS: About one in four individuals was involved with the justice system during the two-year period. The justice-involved group incurred costs approximately double those of the group with no involvement-$48,980 compared with $24,728 per person. Costs were shared by several state agencies and Medicaid. DMHAS bore the largest proportion of state service costs, covering 49% of total costs for persons with justice involvement and 69% of costs for those without involvement. CONCLUSIONS: Criminal justice involvement is a complex and costly problem that affects a substantial proportion of adults with serious mental illness who receive services across state agencies. Applying per-person cost estimates in other states could help mental health and criminal justice systems to better plan, coordinate, and deliver cost-effective services to individuals with serious mental illness who become involved with the criminal justice system.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".