Roots of Resilience: Navigating Métis Education Across Generations in Saskatchewan
Bibliographic record
Abstract
Historically, Métis people in Saskatchewan have had to embody resilience and fortitude to withstand systemic oppressions and colonialism, particularly within educational institutions (Boyer & Chartrand, 2022; Gillies, 2021; Racette & Sammel, 2020). The release of the Truth and Reconciliation Commission of Canada’s Calls to Action in 2015 sparked a movement of accountability across societal realms to address the historical and ongoing injustices inflicted upon Indigenous peoples (Deer, 2022; Hare, 2022; Kovach, 2021), underscoring the timeliness of this research. To disrupt the underrepresentation of Métis perspectives and the cultural homogenization prevalent within the literature (Kearns & Aniuk, 2015; Scott, 2021), I draw upon my family’s intergenerational resilience as racialized Métis learners to explore how they resisted the colonial agendas that sought to diminish them. This study employed a distinctive Métis methodological approach, informed by critical Métis studies and guided by a multi-generational Métis flower beadwork relational framework. Through this lens, I examine how westernized ideologies and Saskatchewan’s provincial education systems have historically shaped, and continue to shape, the experiences of racialized Métis learners in the province, and how these experiences have had enduring impacts. Drawing upon conversations with five of my Métis family members, the study illuminates both the persistent challenges that call for more equitable and inclusive learning environments, and the progressive transformations within Métis K-12 education as Métis visibility and recognition continue to grow.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".