Bibliographic record
Abstract
Abstract Mental health courts are a type of criminal justice reform that aim to divert defendants with severe mental illness away from incarceration, to facilitate their access to psychiatric treatment and to prevent recidivism. The courts assume that mental illness is a driver of criminal offense and hence access to treatment will protect public safety and improve defendants’ psychological well-being. Defendants agree to mandatory behavioral health interventions, case management, and community supervision (typically probation) through a judicial structure derived from drug courts. The courts feature (a) nonadversarial relations between judge and defendant, (b) a unified court team comprising legal, penal, social work, and mental health professionals, (c) linkages with community providers of psychiatric and addiction treatment, and (d) regular court appearances where the judge oversees defendants. The courts reflect the problem-solving justice movement and its goal of ameliorating the root causes of offending. They also embody principles of therapeutic jurisprudence through judges’ empathetic colloquies with defendants. Founded in the United States (1997) and Canada (1998), mental health courts offer a novel response to the crisis of mass incarceration and the retrenchment of public mental health services. They embody liberal goals of incremental change by providing an alternative to jails and prisons but without radically reengineering the entire criminal justice system. Although the courts do moderately reduce recidivism and the severity of future offenses, they have been criticized on several grounds. Criminal psychologists claim psychiatric illness has only an indirect effect on offending, and that the courts’ efficacy comes from their pragmatic efforts (connecting people to housing and welfare supports) and not psychiatric treatment. Other critics state that mental health courts do not address the basic causes of mass incarceration and simply reproduce the state’s punitive impulse under the guise of reform.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".