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Record W2917118742 · doi:10.1177/0840470418808815

Trends in mental health system transformation: Integrating youth services within the Canadian context

2019· article· en· W2917118742 on OpenAlexafffundabout
Tanya Halsall, Ian Manion, Srividya N. Iyer, Steve Mathias, Rosemary Purcell, Joanna Henderson

Bibliographic record

VenueHealthcare Management Forum · 2019
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental HealthSpinal Cord Injury BCUniversity of OttawaUniversity of British ColumbiaOntario Centre of Excellence for Child and Youth Mental HealthMcGill UniversityDouglas Mental Health University InstituteRoyal Ottawa Mental Health Centre
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Ottawa
KeywordsMental healthContext (archaeology)Promotion (chess)Integrated servicesPublic relationsBusinessKnowledge managementPsychologyPolitical scienceComputer sciencePsychiatryGeographyPolitics

Abstract

fetched live from OpenAlex

The current mental health services system in Canada is fragmented and transitions between the youth and adult mental health systems have been identified as needing significant improvement. Integrated Youth Services (IYS) are designed to be adaptable and developmentally appropriate as well as to promote seamless transitions, including during emerging adulthood. This article provides an overview of recent developments in Canadian mental health system transformation to promote the integration of services and the holistic promotion of youth well-being. We offer an overview of the current state of knowledge related to best practices in IYS in Canada and highlight areas for future development. We also introduce Frayme, a Canadian-based international knowledge translation platform designed to connect organizations working in the youth services system to accelerate the implementation of IYS.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.923

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.014
Science and technology studies0.0090.003
Scholarly communication0.0080.004
Open science0.0030.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.037
GPT teacher head0.352
Teacher spread0.315 · 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 designObservational
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

Citations88
Published2019
Admission routes3
Has abstractyes

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