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Community treatment orders: the ethical balancing act in community mental health

2009· article· en· W1988355616 on OpenAlexafffund
Nicole Snow, Wendy Austin

Bibliographic record

VenueJournal of Psychiatric and Mental Health Nursing · 2009
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsNewfoundland and Labrador Centre for Applied Health ResearchUniversity of Alberta
FundersOntario Ministry of Health and Long-Term Care
KeywordsMental illnessMental healthCompliance (psychology)Mentally illPsychiatryHuman rightsMedicineMedical emergencyNursingPsychologyPolitical scienceLawSocial psychology

Abstract

fetched live from OpenAlex

Community treatment orders (CTOs) are legal mechanisms by which an individual with a mental illness and a history of non-compliance and potential for violence can be mandated (against their will) to undergo psychiatric treatment in an outpatient setting. Although CTOs are increasingly being adopted by governments as a means of protecting both mentally ill persons and society itself, their use continues to stimulate considerable debate. While there is some evidence of their potential benefits in promoting treatment compliance and reducing hospital stays, there is concern that they infringe on the mental health client's human rights and freedoms. Consideration of the ethical and practical implications of the use of CTOs must continue. In this paper, some of the most pressing issues are identified and discussed.

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)0.046
metaresearch head score (Gemma)0.073
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.046
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.073
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0150.053
Scholarly communication0.0140.015
Open science0.0020.010
Research integrity0.0300.019
Insufficient payload (model declined to judge)0.0030.001

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 head0.050
GPT teacher head0.453
Teacher spread0.404 · 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
GenreCommentary

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

Citations33
Published2009
Admission routes2
Has abstractyes

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