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Record W1968980924 · doi:10.12927/hcq.2015.24116

Improving First-Line Mental Health Services in Canada: Addressing Two Challenges Caused by the Deinstitutionalization Movement

2014· article· en· W1968980924 on OpenAlexaffabout
Jessica Spagnolo

Bibliographic record

VenueHealthcare Quarterly · 2014
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsDouglas Mental Health University Institute
Fundersnot available
KeywordsMental healthBest practiceNursingPolitical sciencePsychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The deinstitutionalization movement in Canada began in the 1960s. It is defined as the process of discharging chronic mental health patients into the community in order for them to receive care from community mental health services. The deinstitutionalization movement is failing in Canada at this time for two main reasons: (1) the provinces' community mental health programs lack integration; and (2) the negative stigma attached to mental illness is still present in the community. This article will discuss ways to ensure the integration of first-line mental health services and the elimination of stigma through organizational and systemic changes in Canada.

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)0.009
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: Empirical · Consensus signal: none
Teacher disagreement score0.171
Threshold uncertainty score0.962

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0170.006
Scholarly communication0.0070.002
Open science0.0030.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.346
Teacher spread0.305 · 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
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

Citations3
Published2014
Admission routes2
Has abstractyes

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