WHITEMUD: A NARRATIVE INQUIRY INTO THE EXPERIENCE OF SELF-IDENTIFYING MÉTIS EDUCATORS
Bibliographic record
Abstract
This narrative inquiry explores lived life experiences of two Métis educators and the role their culture had in their identity as teachers. The research wonders of this thesis asked the following questions: What role did the Métis culture have in shaping your identity? How does your cultural identiy affect your role as a student, as a teacher, and as an administrator? What are some challenges did you face as Métis people in an educational context (as students, teachers, and administrators)? Derived from individual semi-structured interviews ranging from 45 minutes to one hour, a narrative account of each teacher is presented and their storied lives are inquired into within the three dimensional inquiry space, defined to include the three commonplaces that are essential to narrative inquiry: temporality, sociality, and place (Clandinin & Connelly, 2000). In this research, the participants shared their experiences while I analyzed their stories in the larger context of Métis identity and considered several strands: curriculum, relationality, poverty, and cleanliness. The strands arose from analysis of the conversations and are followed by discoveries and future implications in regards to Métis teacher identity. Discoveries include a need for the revitalization of the Michif language, immersion of Métis culture into the curriculum, and the uniqueness of the Métis culture. Future implications include a further investigation into the effects of anxiety and nervousness from colonization, as well as continued study of the Métis culture as it evolves moving forward.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.017 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| 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".