Self-determination in health: a road to community wellness? A critical look at Island Lake's evolving model of health service delivery
Bibliographic record
Abstract
The disproportionate burden of disease in the Aboriginal population in Canada has become so great that it is now being referred to as a health ‘crisis’. Evidence suggests that the answer to these ills lies not in the western biomedical model of heath care, but within the Aboriginal traditions of self-determination and holism (RCAP, 1996; O’Neil, Lemckuk-Favel, Allard & Postl, 1999; Romanow, 2002; CIHI, 2004; Maar, 2004; First Nations & Inuit Regional Health Survey, 2004). To this end, First Nations communities have been negotiating with the federal government and transferring responsibility for their community-based health services since 1986, despite the limitations of the federal Health Transfer Policy (Gregory, Russell, Hurd, Tyance & Sloan, 1992; Lavoie, et al, 2005; RCAP, Vol 3, Chp 3, 1996; Speck, 1989). These self-determination initiatives in health attempt to improve the health status of community members. Thus, determining an approach to health service delivery that contributes to positive health outcomes is of particular significance. Examining Island Lake’s evolving model of health service delivery indicates the success of the intergovernmental, interdepartmental, and intersectoral partnership approach they have taken; as evidenced by the Regional Renal Health Program, with dialysis treatment services, that has been established, perhaps for the first time in the country, in a remote First Nations community without existing hospital services. There remains work to be done in creating a holistic system of health service delivery that reflects their unique worldview within a context of health promotion and self-determination; however, their accomplishments to date, established processes, willingness to put their dreams into action and build what has not been built before demonstrate a potential to improve community health and well-being.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.041 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 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".