How do health, spirituality and well-being intersect in the Métis Nation of Alberta (MNA) Region 3? A Métis-guided, community-based, participatory study
Bibliographic record
Abstract
OBJECTIVES: The purpose of our research was to understand intersections between health, spirituality and well-being in the Métis Nation of Alberta (MNA) Region 3. DESIGN: This Métis-guided, community-based, participatory research builds on our previous patient-oriented community-based study where we co-developed a qualitative structured survey with leaders, Elders and community members to explore health, spirituality and well-being in the MNA Region 3. SETTING: Métis people are affected by historical and contemporary impacts of colonisation. This includes the residential school experience, impacting how Métis people relate to themselves, to others and to their culture. Alberta has the highest Métis population in Canada, and our research is based in the most densely populated region. PARTICIPANTS: 101 surveys were completed between September and November 2021, via Qualtrics. Twenty-five participants who completed surveys participated in community-based participatory research sharing circle data analysis groups in January 2022, via Zoom. RESULTS: Six overarching themes were developed in our participatory data analysis: (1) searching, (2) interconnectedness, (3) colonisation and systems, (4) traditional practices and teachings, (5) spiritual and religious practices and (6) relationship with Métis identity. CONCLUSIONS: We discovered multiple intersections between health, spirituality and well-being within the MNA Region 3. Our results indicate that the impacts of colonisation for Métis people are poorly understood. More research is needed to understand the ongoing impacts of colonisation, including increased understanding about Métis identity, health, spirituality, religion and well-being. In particular, more research is needed about the effects of intergenerational trauma in the broader MNA, and across Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".