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Record W2073378445 · doi:10.1332/174426409x437892

Embedding evidence-based practice in child and youth mental health in Ontario

2009· article· en· W2073378445 on OpenAlexaffabout
Ian Manion, Don H. Buchanan, Michael Cheng, Joanne Johnston, Kathy Short

Bibliographic record

VenueEvidence & Policy · 2009
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsHamilton Health SciencesMental Health Research CanadaUniversity of OttawaOntario Centre of Excellence for Child and Youth Mental HealthChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsMental healthPublic relationsInformation sharingPoliticsService (business)Knowledge sharingKnowledge managementPolitical scienceBusinessMedicinePsychiatryMarketing

Abstract

fetched live from OpenAlex

This article describes recent trends in the province of Ontario (Canada) and beyond that have begun to create a readiness to bring research to practice in children’s mental health. The experience of developing innovative cross-sectoral partnerships in Ontario that facilitate the linkage of research and service is discussed. The Child and Youth Mental Health Information Network is profiled as an emerging collaboration that epitomises such partnerships, and the key knowledge exchange activities of the five partner organisations are described. The article highlights the importance of engaging all levels of the system – clinical, supervisory, management, community, policy and political – in order to create a culture change that truly supports the sharing of information and the process of embedding evidence-based practice in services for children and families. This is a descriptive article that outlines key complementary knowledge exchange activities of each of the partners while highlighting joint initiatives and the value added of the Network.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.480
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.097
GPT teacher head0.467
Teacher spread0.370 · 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 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

Citations6
Published2009
Admission routes2
Has abstractyes

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