Exploring health and wellness with First Nations communities at the “Knowing Your Health Symposium”
Bibliographic record
Abstract
Indigenous older adults living in rural communities require accessibility to and readiness for new technologies to support the monitoring of health data and health status, as well as dementia education. Morning Star Lodge partnered with the File Hills Qu'Appelle Tribal Council, a Community Research Advisory Committee and All Nations Hope Network to bring a diverse group of First Nations community members to the "Knowing Your Health Symposium" to learn about traditional health and First Nations' wellness. Indigenous research methods and community-based involvement informed and guided the research. An environmental scan was conducted relating to co-researchers' nutrition, exercise, and self-management of health and health issues through an anonymous survey distributed at the symposium. The purpose of the symposium was to provide communities with information about healthy lifestyles as it relates to dementia and equip community members with the ability to make constructive decisions regarding their health.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.028 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".