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Record W4391096757 · doi:10.7870/cjcmh-2023-030

Black Youth Mentorship: Project Artemo and Opportunities for Proactive Cross-Sector Mental Wellness Support

2023· article· en· W4391096757 on OpenAlexaffvenueabout
Mia Tulli-Shah, Odion Welch, Emmanuel Onah

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMentorshipMental healthFocus groupPsychologyStigma (botany)Qualitative researchMedical educationIntersectionalityMedicineSociologyPsychiatryGender studies

Abstract

fetched live from OpenAlex

In this qualitative study, researchers interviewed 10 participants (five mentees and five mentors) of the 2020–2021 Artemo Black Youth Mentorship program session. The Artemo program takes place with Black youth across Alberta, with a focus in Edmonton, Calgary, and Fort McMurray. The program focuses on providing supports for a mental health preventative approach, employment/educational supports, and a gender intersectionality focus throughout Alberta. To assess the program, organizers hired an independent researcher to maintain anonymity. Findings from the interviews spoke to larger themes related to Black youth mental health and well-being, as well as community-based approaches to supporting them. Our findings offer three key themes. First, youth offered their own perceptions of mental wellness. Second, they explained stigma, a lack of cultural competency and representation among service providers, and financial costs, as significant barriers to mental health and wellness. Third they discussed opportunities for youth mentorship to fill service gaps and act as a form of resistance. Opportunities include strategies to navigate mental health stigma, opportunities to build trust, benefits of centralizing experiences of race and culture, and benefits of non-medicalized mental wellness support.

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)0.011
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0030.001
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.384
GPT teacher head0.470
Teacher spread0.086 · 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

Citations0
Published2023
Admission routes3
Has abstractyes

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