Everything Is Connected: Integrating First Nations Perspectives and Connection to Land into Population Health Reporting
Bibliographic record
Abstract
For First Nations in Canada, the land reflects a connection to ancestors, the provider of essentials for living, a link to culture and teachings, and a gift for future generations. Due to the centrality of land for First Nations&s; health and wellness, the British Columbia (BC) First Nations Health Authority, in collaboration with the Provincial Health Officer (PHO), embarked on a journey to honour First Nations&s; connections to land within their population health reports, beyond the highly entrenched Western views of the environment and land. The We Walk Together study was initiated to explore the connections between land, water, and territory as a determinant of health for BC First Nations. Land-based gatherings were held across diverse areas of this Canadian province to enable First Nations Elders, Knowledge Keepers, and youth to share teachings, knowledge, and experiences. The findings reinforced that the complexity of land and human health connections do not fit neatly into the logic of indicators and that Indigenous knowledge systems, which emphasize interdependence and reciprocal stewardship with all of our relations, offer solutions for advancing health promotion, equity, and sustainable development for all.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".