Promoting Diversity in the Recruitment of a Youth Advisory Council in the Mental Health and Addictions System
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".