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Record W4403500194 · doi:10.26522/ssj.v18i3.4246

Challenging Involuntary Treatment and Confinement in Canada Through the United Nations Convention on the Rights of Persons with Disabilities (CRPD)

2024· article· en· W4403500194 on OpenAlexafffundvenueabout
Russell Rozinskis, Chloe Rourke

Bibliographic record

VenueStudies in Social Justice · 2024
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsMcGill UniversityYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsConvention on the Rights of Persons with DisabilitiesPolitical scienceConventionLaw and economicsLawEconomics

Abstract

fetched live from OpenAlex

The Convention on the Rights of Persons with Disabilities (CRPD) came into force in 2008. People with disabilities, including people with psychosocial disabilities, were instrumental to its development. Article 12 and Article 14 of the CRPD, which respectively affirm the universal legal capacity and right to liberty of persons with disabilities, were viewed as key victories by disability rights movements. These provisions are particularly important for people with psychosocial disabilities who are routinely subjected to human rights violations through psychiatric detainment and involuntary treatment authorized under domestic mental health legislation in many states. We aim to advance discourse surrounding the CRPD and its development by centring mad peoples’ voices and individuals with lived experience through a literature review and interviews with key disability rights advocates. Using Canada as a case study, we critically examine the implementation of the CRPD and the need to align mental health acts with our international human rights obligations. We argue that forced psychiatric interventions violate the rights of persons with psychosocial disabilities and cause inherent harm. There is an urgent need to move towards new paradigms of care that promote the dignity and autonomy of people with psychosocial disabilities.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.423
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.137
GPT teacher head0.421
Teacher spread0.284 · 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 teacher head, 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
Published2024
Admission routes4
Has abstractyes

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