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Record W2102571759 · doi:10.1177/0829573512468859

Challenges and Solutions in the Implementation of the School-Based Pathway to Care Model

2013· article· en· W2102571759 on OpenAlexaffabout
Stan Kutcher, Yifeng Wei

Bibliographic record

VenueCanadian Journal of School Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMental healthService providerPsychologyImplementationWork (physics)Health careMedical educationNursingService (business)MedicineComputer sciencePsychiatryPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Most mental disorders often onset during the adolescent years, providing opportunities for educators, health care providers, and related stakeholders to work collaboratively in addressing adolescent mental health care needs. This report describes early implementations of various components of the School-Based Pathway to Care Model currently applied in Canada, identifies lessons learned, and suggests future directions. The School-Based Pathway to Care Model engages students, teachers, student service providers, parents/families, health care providers, and the wider community through various training programs and both formal and informal linkages between the school, community, and health providers. Preliminary evaluation of the model in whole and in part shows promising outcomes for its application in secondary schools within the wider framework of enhancing system capacity for addressing mental health needs of students. Future focus should be directed towards more rigorous research on the model and its various components.

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)0.065
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.557
Threshold uncertainty score0.891

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0650.063
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.012
Scholarly communication0.0150.008
Open science0.0080.011
Research integrity0.0050.011
Insufficient payload (model declined to judge)0.0040.001

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 head0.064
GPT teacher head0.327
Teacher spread0.263 · 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 designQualitative
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

Citations28
Published2013
Admission routes2
Has abstractyes

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