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Record W4408124013 · doi:10.1111/hex.70208

Promoting Diversity in the Recruitment of a Youth Advisory Council in the Mental Health and Addictions System

2025· article· en· W4408124013 on OpenAlexaff
Deewa Anwarzi, Thalia Phi, Roula Markoulakis

Bibliographic record

VenueHealth Expectations · 2025
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of TorontoMcMaster UniversitySunnybrook Hospital
Fundersnot available
KeywordsMental healthDiversity (politics)Inclusion (mineral)Plan (archaeology)Public relationsAddictionEquity (law)PsychologySociologyPolitical sciencePsychiatrySocial psychologyGeography

Abstract

fetched live from OpenAlex

INTRODUCTION: There is increasing interest in youth advisory councils (YACs) within the mental health and addictions (MHA) system; however, little is known about methods to ensure diversity of perspectives on these councils. Diverse perspectives are critical for ensuring that youth MHA organizations are equipped to support youth needs. METHODS: A youth-led YAC recruitment initiative was developed and implemented at a GTA-based youth MHA navigation service: the Family Navigation Project. RESULTS: Specifically, this paper highlights the efforts of three youth staff and volunteers who championed a YAC recruitment plan focused on promoting equity, diversity, inclusion (EDI) and accessibility, youth engagement (YE), and lived experience/expertise (LE). DISCUSSION: This paper is written from the perspective of the youth recruitment team and provides important insights for MHA services interested in ensuring EDI, accessibility, YE and LE on a new or existing YAC, and researchers studying YE in MHA care.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.455
GPT teacher head0.442
Teacher spread0.013 · 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 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

Citations2
Published2025
Admission routes1
Has abstractyes

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