The Métis Nation of Saskatchewan: Building Towards Self-Governance
Bibliographic record
Abstract
Indigenous and western qualitative research methods are used to examine whether there is a the relationship between Métis perspectives to increase the Métis Nation - Saskatchewan (MN-S) citizenship registry and the implementation of good governance. Good governance was operationalized by conducting a literature review that identified five universal principles of good governance in the literature. An analysis of the MN-S governance documents was completed using the universal principles of good governance. The study shows that in semi-structured conversations with Métis people about increasing the Métis citizenship registry, broader principles of governance were always implicated. It is incumbent upon the MN-S and other Métis governance organizations to cultivate good governance practices in keeping with the expectations of Métis citizenry and to meet demands for greater sophistication and skill in negotiating with the Canadian state in the rapidly changing Métis public policy landscape. The study concludes that while the experience of Métis people with colonization has been punctuated with systemic racism and marginalization through public policies, in contemporary times, Saskatchewan Métis must participate in the process of self-determination to ensure that Métis governance organizations such as the MN-S are legitimate representatives. This study also has implications for a policy on reconciliation, as the field research demonstrates that Métis perspectives invoke a much broader scope for articulating a policy on reconciliation than the current state-Indigenous dichotomy articulated by the Government of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".