"A spoke in the wheel": Understanding experiences of 'Métis Red River Jig' dancers and impacts of the Métis Red River Jig on health and well-being
Bibliographic record
Abstract
Indigenous Peoples in Canada have experienced disruptions in cultures, traditions, identities, and social and community structures through centuries of ongoing colonization and assimilation. The Metis Red River Jig dance is important in maintaining and extending community ties, has survived the cultural genocide aims of colonization, and continues to thrive. This dance combines Plains First Nation, Scottish, Irish, Scandinavian and French-Canadian dance forms in alternating sections of the double step and varied fancy steps. The purpose of this study was to understand the experiences of Red River Jig dancers and impacts of Red River Jigging on their health and well-being. In partnership with Li Toneur Niimiyitoohk Metis Dance group, this narrative inquiry used conversational interviews to hear stories from ten Red River Jiggers (6 females; 20-62 years), proficient in dancing the double step. Stories were audio-recorded, transcribed verbatim and reflexive thematic analysis (Braun & Clarke, 2019) conducted. Four themes were created from stories shared to understand how dancing the Red River Jig influences health and well-being: (1) It's the bonding, building community, and strengthening: Red River Jigging is community; (2) Heightened sense of pride and awareness: Embracing and reclaiming culture and identity; (3) You have to utilize your mind, body and spirit: A spoke in the wheel of wholistic health and; (4) Dancing has kept me sober: Therapy and healing from historic trauma. These findings support cultural traditions including the Red River Jig as vital to restoring cultural identity and facilitating Indigenous Peoples' physical, mental, emotional and spiritual health and well-being.Acknowledgments: Saskatchewan Health Research Foundation (SHRF)
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.020 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".