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Just in time: how evidence-on-demand services support decision making in Ontario’s child and youth mental health sector

2015· article· en· W2793829446 on OpenAlexaffabout
MaryAnn Notarianni, Purnima Sundar, Charles W. Carter

Bibliographic record

VenueEvidence & Policy · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsOntario Centre of Excellence for Child and Youth Mental HealthHealth Canada
Fundersnot available
KeywordsMental healthExcellenceEvidence-based practicePublic relationsPsychologyEvidence-based policyBusinessMedicinePolitical sciencePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

Using the best available evidence to inform decision making is important for the design or delivery of effective health-related services and broader public policy. Several studies identify barriers and facilitators to evidence-informed decision making in Canadian health settings. This paper describes how the Ontario Centre of Excellence for Child and Youth Mental Health, as an intermediary organisation, facilitates evidence-informed decision making at organisational and system levels in Ontario’s child and youth mental health sector through two unique knowledge mobilisation services. This paper describes these services, offering them as exemplars for other sectors seeking to support evidence use in policy and practice decision making.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.162
GPT teacher head0.463
Teacher spread0.300 · 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.

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

Citations1
Published2015
Admission routes2
Has abstractyes

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