Exploring Indigenous youth perspectives of mobility and social relationships: A Photovoice approach
Bibliographic record
Abstract
Abstract Growing rates of urbanization among young Indigenous populations have been associated with frequent geographic mobility between urban and rural areas, as well as within cities. Little is known of the context of this mobility, or its impacts on social relationships. With nearly half the urban Indigenous population under the age of 25, gaps persist in understanding the mobility experiences of Indigenous youth, who tend to be more mobile than non‐Indigenous youth and move more often than their older counterparts. The voice of Indigenous youth remains under‐represented, and research with mobile Indigenous youth is limited. To address these gaps, Photovoice was used to better understand how mobility shapes social relationships among a group of Indigenous youth living in Winnipeg, Manitoba. Key findings reveal mobility is common and persistent, often rooted in colonization and intergenerational trauma. As a result, this mobility is often linked to unstable living conditions and displacement from family and social connections. The frequent and uncertain nature of this mobility impacts the ability to develop and sustain positive and supportive social relationships. Findings point to the importance of culturally safe spaces and Indigenous mentorship that fosters resilience and self‐empowerment.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".