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Record W2346255544 · doi:10.7870/cjcmh-2015-017

Special Issue Mobilizing Canada's Mental Health Strategy Introduction

2015· article· en· W2346255544 on OpenAlexaffvenueabout
Steve Lurie, Gillian Mulvale

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2015
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsMcMaster UniversityCanadian Mental Health Association
Fundersnot available
KeywordsMental healthCommissionMental illnessHealth carePolitical scienceHealth policyPublic administrationMedicinePublic relationsPsychiatryLaw

Abstract

fetched live from OpenAlex

Until 2012, Canada was the only G7 country without a national mental health strategy.Changing Directions, Changing Lives (the Strategy) was developed by the Mental Health Commission of Canada (MHCC) (2012) over a 4-year period.The Strategy reflects extensive consultation with Canadians, including many who care passionately about the state of mental health services in our country.It grew out of the work of the Senate Committee on Social Affairs, Science and Technology, which published the report Out of the Shadows At Last: Transforming Mental Health, Mental Illness and Addiction Services in Canada (Kirby & Keon, 2006) almost 10 years ago.Out of the Shadows called for major reforms to mental health care delivery, a mental health transition fund of $5.3 billion and a mental health commission to guide the reform.The creation of the MHCC and the release of the Strategy are key milestones in mental health policy in Canada, but Canada continues to have lower rates of spending on mental health than the UK, Australia, and New Zealand.

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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.489

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0110.003
Scholarly communication0.0140.004
Open science0.0040.004
Research integrity0.0180.008
Insufficient payload (model declined to judge)0.0650.010

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 head0.244
GPT teacher head0.424
Teacher spread0.179 · 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
GenreEditorial

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

Citations1
Published2015
Admission routes3
Has abstractyes

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