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Record W4385747400 · doi:10.59962/9780774827003-002

Introduction

2013· book-chapter· en· W4385747400 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of British Columbia Press eBooks · 2013
Typebook-chapter
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

These are indeed "interesting times" to be working in the mental health field.In Canada, as we move through the second decade of the twenty-first century, we have seen the locus of treatment shift from institutions to the community, as the "asylums" -the provincial psychiatric hospitals -downsize and finally close.We have also seen a Canadian Senate report on mental health reform, Out of the Shadows at Last, give rise to the Mental Health Commission of Canada, a federal advisory body whose mission is "to promote mental health in Canada, and work with stakeholders to change the attitudes of Canadians toward mental health problems, and to improve services and support." 1 We have seen what is called the recovery vision being written about extensively, and its principles adopted by the Mental Health Commission as the basis for a more positive, holistic approach to mental health care, one that moves beyond what has been seen as the narrow confines of the "medical model."We have seen better mental health housing and employment models developed, with persons with serious mental disorders now employed within health authorities as peer workers, committee members, and program leaders.However, despite these promising developments, problems have persisted.Persons with serious mental disorders are overrepresented among the homeless and in the criminal justice system.Many are not in treatment.Stigma -discrimination from the general public -does not seem to be diminishing.A Canadian Psychiatric Association position paper concludes that: "The promise of deinstitutionalization has not been realized.Hospital bed closures have been too rapid and too extensive.Community resources remain underfunded and limited.Fragmentation in the health care system has meant that no one has taken responsibility for the care of one of the most disadvantaged and marginalized populations" (Chaimowitz 2012, 5).Whether or not this statement is completely accurate, what is noteworthy is that it was written

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.475
Threshold uncertainty score0.748

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.4750.247

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 head0.019
GPT teacher head0.215
Teacher spread0.196 · 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.

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
Published2013
Admission routes1
Has abstractyes

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