Nehiyawak (Cree) women’s strategies for aging well: community-based participatory research in Maskwacîs, Alberta, Canada, by the Sohkitehew (Strong Heart) group
Bibliographic record
Abstract
Abstract Background The Sohkitehew (Strong Heart) Research Group, which included an Elders Advisory Committee of seven Nehiyawak (Cree) women, set out to bring Maskwacîs community members together to understand Nehiyawak women’s experiences of “aging well”. The goals of this research were to generate information honouring Indigenous ways of knowing, and gather strengths-based knowledge about aging well, to help Maskwacîs, women maintain wellness as they age. Methods We facilitated qualitative Sharing Circles in three different settings in Maskwacîs. Discussions were prompted using the four aspects of the self, guided by Medicine Wheel teachings: Physical, Mental, Emotional, Spiritual. Detailed notes were recorded on flip charts during the discussions of each Sharing Circle. Data were analysed using descriptive content analysis to identify practical strategies for aging well. Results Thirty-six community members attended one or more Sharing Circle. Strategies included: Physical—keeping active to remain well; Mental—learning new skills to nourish your mind; Emotional—laughing, crying, and being happy; Spiritual—practicing Nehiyawak traditional ways. Participants commented that balancing these four aspects of the self is necessary to achieve wellness. Following the analysis of the Sharing Circle comments, three community feedback sessions were held to discuss the results in the wider community. These strategies were formatted into a draft booklet which incorporated Cree language, and archive photographs of Maskwacîs women and families. Conclusions The Nehiyawak Sharing Circles identified practical strategies that help women to remain well as they age. This positive approach to aging could be adopted in other Indigenous and non-Indigenous communities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".