From Breath to Beadwork: Lessons Learned From a Trauma- Informed Yoga Series With Indigenous Adolescent Girls Under Youth Protection
Bibliographic record
Abstract
This paper explores the promising practice of an emerging culturally adapted, trauma-informed yoga program for Indigenous adolescent girls. I draw from my experiential learning during a series of 12 yoga sessions over 2018 and 2019 with eight Indigenous girls (ages 13–17) from rural and remote Inuit communities in Quebec, Canada. Participants had experienced varying degrees of child maltreatment and interaction with the child welfare system, and they were all under the care of youth protection services in a residential facility. The yoga and mindfulness intervention provided weekly 60-minute sessions in the residential unit. Yoga sessions integrated a blended model of cultural teachings, group dialogue, and trauma-informed yoga. The approach included circle sharing, cultural teachings, gentle progressions of physical postures, guided meditation, breathing techniques, centring practices, and beadwork. This promising practice explores trauma-informed yoga as a strengths-based community strategy for relational healing that promotes cultural connectedness, safety, and resilience among Indigenous adolescent girls removed from their rural and remote communities to a residential facility in an urban area. This paper outlines an introductory framework for health professionals, paraprofessionals, program administrators, and staff working with Indigenous children and youth in residential facilities. Specifically, this promising practice builds on existing findings of trauma-informed yoga with adolescents, as well as movement and centring approaches through an Indigenous lens of relational healing.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".