Metis Nation of Alberta (MNA): collaborative research practices and procedures
Bibliographic record
Abstract
Metis 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 the 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 the disease burden and experiences among First Nations; however, little work has been done to understand the Metis health inequalities and experiences. The MNA prioritized the development of health evidence and 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 remained in control of data and research priorities. How can health evidence empower the MNA? How can these partnerships be meaningful overtime? An information sharing agreement was signed in 2010, with the first report Health Status of the Metis Population of Alberta developed in 2012 and 3 follow up reports on Injuries, COPD, and Cancer. With the evidence in these reports, the MNA advocates for equitable health resources for Metis people in Alberta, and the Ministry of Health continues to meet their mandate for developing health evidence. When empowered to take ownership of developing health research, the MNA is an equal partner with government and local universities, and successful partnerships develop. Identified in the research are the unique health profiles of Metis people, which are integral evidence for the development of appropriate health services. Prior to the establishment of these relationships, there was little to no research on the health outcomes of Metis people, and now there is a foundation for continued collaboration to expand knowledge on this distinct Nation of people. Key messages: Collaboration with Government and University empowers Indigenous community. Long-lasting partnerships for continuous minority research health initiatives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.277 | 0.158 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.010 | 0.017 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".