Understanding how leadership experience affects the educational attainment, employability, and wholistic wellness of Indigenous youth in Canada: a qualitative study
Bibliographic record
Abstract
The Indigenous Youth Mentorship Program (IYMP) is a youth-centred, community-based programme that fosters wholistic wellness and mino-pimâtisiwin ('the good life' in Cree) within Indigenous communities across Canada. IYMP uses a communal mentorship model, where Indigenous high school students, supported by programme leaders, facilitate healthy living activities for elementary-aged peers. This culturally grounded setting promotes leadership development, life skills, and community engagement. While youth leadership experience is known to influence education, employment and wellness, the culturally specific impact of IYMP on youth mentors remains underexplored. This study aimed to amplify youth voices to understand youth mentors' perspectives on how leadership experience, through IYMP, impacts their education, employment, and wholistic wellness. Focused ethnography was used as the guiding method. IYMP youth mentors (aged 14-19) were purposively recruited. Talking circles were the primary data generation tool, with 21 participants across three circles (n = 5, n = 10, n = 6). Sessions were held in person, audio-recorded, and transcribed. Unstructured participant observations, documented as field notes, were used to supplement and contextualize the data. Thematic analysis was used to identify patterns within the data. Participants reported that leadership experiences enhanced their confidence and communication skills, which made school more enjoyable, improved employability, and impacted their wholistic wellness through healthy behaviours and strong social networks. Earning high school course credits through IYMP was a key motivator, making leadership more accessible and supporting high school completion. IYMP strengthens youth mentors' educational attainment, employability, and wellness by weaving together leadership experiences with the development of communication skills and confidence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".