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Record W4234256733 · doi:10.32920/ryerson.14641461

The Role of Competence in Outcomes for Children and Youth: An Approach for Mental Health

2021· preprint· en· W4234256733 on OpenAlexaboutno aff
Carol Stuart, William M. Carty

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsCompetence (human resources)Mental healthPsychologyBest practiceMedical educationEvidence-based practiceMedicineSocial psychologyPsychotherapistPolitical scienceAlternative medicine

Abstract

fetched live from OpenAlex

Executive Summary The primary goal of this project was to establish what exists in the education and training of entry-level child and youth care (CYC) practitioners in Ontario regarding evidence-based competencies focusing on mental health issues. To determine how CYC practice and evidence-based treatment and practices are related the project examined what competencies are required in CYC practice, what competencies are required in CYC practice specific to mental health practice, and how college and university education programs are training CYC practitioners to implement evidence-based practices. Additionally the project provided forums for educators and mental health providers to discuss their impressions, ideas and beliefs as to what future strategies are required to ensure that CYC education and practices are evolving to include the skills necessary to implement evidence-based treatments and practices (EBT and EBP).

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)0.021
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.125
Threshold uncertainty score0.248

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0050.010
Scholarly communication0.0090.006
Open science0.0020.006
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.073
GPT teacher head0.443
Teacher spread0.369 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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