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Record W3024833067 · doi:10.1002/9780470061589.fsa285

Mental Health Courts

2009· other· en· W3024833067 on OpenAlexaff
Richard D. Schneider

Bibliographic record

VenueWiley Encyclopedia of Forensic Science · 2009
Typeother
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCriminalizationMental healthTherapeutic jurisprudenceMental healthcareEconomic JusticePsychologyCriminologyHealth careMental health lawLawSociologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Abstract Mental health courts have been instrumental in bringing our attention to the plight of mentally disordered accused. While not flawless, they represent an innovative approach to addressing the needs of individuals within our society who have historically been alienated by both the justice system and the increasingly debilitated and diluted mental healthcare system. Above all aspects of the mental health court movement, perhaps the most laudable feature is the commitment to see new and improved ways to address these needs. They are a first attempt, a good attempt, and an example of therapeutic jurisprudence at work in reducing the criminalization of the mentally disordered individual. A much more direct and expedient approach to the problems sought to be addressed by these courts is deceptively simple: reinvest in the mental healthcare system so that that the needs of these individuals would be addressed at first instance. Absent a major change in this regard, mental health courts continue to be brave and innovative attempts to patch a broken system.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.147
Threshold uncertainty score0.492

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.002
Scholarly communication0.0080.002
Open science0.0010.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.1470.018

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 head0.015
GPT teacher head0.315
Teacher spread0.301 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

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