“Community traditions, community kinship, language, and land bring me a lot of joy”: the importance of culture and social support in the health and wellbeing of Métis people
Bibliographic record
Abstract
Canada legally recognizes three Indigenous identities: First Nations, Inuit, and Métis. Métis People are a distinct Indigenous nation with unique history, culture, and traditions. Historic and ongoing colonization and assimilation policies negatively affect Indigenous Peoples’ mental, physical, emotional, cultural, and social health. Colonization and assimilation impacts on Métis People specifically are unclear, but health impacts and experiences differ from First Nations’.Objective The purpose of this narrative study was to understand Métis adults’ stories of culture and social support in relation to their health and wellbeing.Methods In partnership with Saskatoon Métis Local 126, 19 adults (9 females, 30 ± 11 years) participated in conversational interviews and photovoice reflections.Results Four themes represent the importance of culture and social support to Métis People’s health: 1) Métis Identity: “It was really empowering to learn about where I come from”; 2) Kinship, Community, and Culture: “Métis are people who gather”; 3) The Métis Environment and Land Connection: “Where I go to recharge”; 4) Knowledge, Impacts, and Intentional Steps for the Future: “Taking what’s good and making that in a way forward”.Conclusions Culture and social support are important protective factors in facilitating positive health outcomes for Métis People.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".