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Record W3205792654 · doi:10.29173/mlj995

Manitoba's Mental Health Court: A Consumer Perspective

2017· article· en· W3205792654 on OpenAlexaboutno aff
Joshua Watts, Michael Weinrath

Bibliographic record

VenueManitoba Law Journal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Mental healthPsychologySociologyPsychiatryComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Mental health courts (MHC) have been growing in popularity and use in Canada and elsewhere and are lauded as a humane mechanism to divert those with mental health conditions away from the formal justice system.Research to date has tended to focus on process questions of proper referral and quantitative outcomes of reoffence rather than on feedback from the consumer, the program participant.We report findings from a mixed methods study of mental health court participants (N=20) and use numeric rankings as well as narrative responses to present client perspectives.Findings were generally favourable towards mental health court staff and programming, though some areas were rated higher than others.Feelings of procedural fairness were high, and the use of rewards and sanctions was endorsed.Some concerns about the coercive nature of the program, however, were also expressed by participants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0240.009
Scholarly communication0.0100.003
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.000

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.

Opus teacher head0.038
GPT teacher head0.346
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2017
Admission routes1
Has abstractyes

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