2.1-O3Type 2 diabetes in the Métis population of Alberta, Canada: a mixed methods study
Bibliographic record
Abstract
Métis people are a distinct Indigenous people in Canada, and are a culture that evolved out of the unions between European traders and First Nations women. These unions created a distinct cultural, political, and self-governing people, and are recognized as one of three rights-exercising Indigenous groups in Canada. Indigenous people in Canada experience a disproportionate burden of chronic disease and poor health outcomes. There have been many studies on disease burden and experiences amongst First Nations; however, little work has been done to understand Metis health inequalities/experiences. The Métis Nation of Alberta (MNA) is the governing body for Métis Albertans and has prioritized research to improve health outcomes for Métis Albertans. To obtain health evidence, the MNA began exploratory discussions with the Ministry of Health in 2007, to utilize administrative health data. University partners were identified to further support with expertise, and the MNA remains in control of data and research priorities. An information sharing agreement was signed in 2010, with four health research projects undertaken over the following six years. With the evidence in these reports, the MNA advocates for equitable health resources for Métis Albertans. The latest health research on Type 2 Diabetes involved a mixed methods study to understand specific health outcomes of the disease amongst Métis Albertans as well as the lived experiences of those with the disease to identify common themes, challenges, and the burden associated with the disease. Métis Albertans have a higher prevalence of the disease and poorer health outcomes related to the disease, which can partially be attributed to a common theme of feeling that health services are not culturally-appropriate and thus inaccessible. The MNA will use these health data to advocate for increased access to culturally-appropriate health services, and specifically, diabetes programs tailored for education, lifestyle changes, and support mechanisms.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".