Transforming First Nations’ health governance in British Columbia
Bibliographic record
Abstract
Purpose The purpose of this paper is to present a study of the transformation of First Nations’ health governance, describing the development of partnerships between First Nations and provincial and federal governments for co-creating solutions to address First Nations’ health inequities in British Columbia (BC). The paper frames this transformation in the context of a Canada-wide reconciliation initiative stimulated by the Truth and Reconciliation Commission. Design/methodology/approach This qualitative case study was a joint initiative between Simon Fraser University and the BC First Nations Health Authority (FNHA), involving interviews with senior leaders within the BC health system, FNHA and First Nations communities. In addition, a policy roundtable was held in February 2015 which gathered 60 participants for further dialogue on the process. Findings Key themes included: partnership and relationships, governance and reciprocal accountability, First Nations perspectives on health and wellness, and quality and cultural safety. Findings indicate that significant transformational changes have happened in the relationship between First Nations and the mainstream health system. The creation of the FNHA has led to more representation for First Nations people at all levels of governance and health service planning, which will ultimately lead to more culturally safe health services that incorporate a First Nations perspective of wellness. Social implications The transformation of First Nations health governance in BC can serve as an example in other indigenous health settings both within Canada and internationally. Originality/value This paper describes a transformative health governance process in First Nations communities that is an historical first in Canada.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.010 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".