Liminality and Mental Health Court Diversion: An Interpretative Phenomenological Analysis of Offender Experiences: Table 1
Bibliographic record
Abstract
Seriously mentally ill people are a ‘revolving-door’ population in criminal justice systems where they cycle in and out of courts and jails. In response and consonant with the principles of therapeutic jurisprudence, mental health courts (MHCs) have flourished in North America and Western Europe in attempts to divert this population away from jail and provision them with the social services they require to avoid legal contact. Little research has focused on the perspective of the accused in MHCs and there has been little information about which aspects of the court and diversion processes contribute to therapeutic processes in MHCs. This qualitative study reports the experiences of nine successful graduates of a Canadian MHC. The data were analysed according to the principles of interpretative phenomenological analysis. The marginality of the accused and their liminal experiences in mental health court diversion are discussed. Social workers have a role to play in the success of clients in diversion and the results of this study may influence service delivery.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".