Nurturing Inuit Education Leadership in Nunatsiavut
Bibliographic record
Abstract
This case study of Inuit teachers, in the Inuit-governed region of Nunatsiavut, is part of a larger research project across Inuit Nunangat examining the preparation, resiliency, and experiences of teachers working in K-12 education. In the past, Inuit who worked in schools were teachers of Inuktitut (Inuit language) or Ilusivut (Inuit crafts and life skills). Now, many Inuit educators are certified teachers who work at all grade levels to infuse Inuit knowledge and pedagogies in Nunatsiavut area schools. In collaboratively exploring the professional lives of teachers, the co-authors examine educators’ dedication to these efforts. Regardless of their position within Newfoundland and Labrador (NL) schools under the Department of Education, these educators are de facto educational and cultural leaders, guiding the next generation with a profound commitment to celebrating and preserving Inuit cultural identity. They engage in self-directed and collaborative professional learning that builds their knowledge and skills in promoting Inuit education. Encouraging a more holistic, practical and meaningful way of teaching that connects to Inuit ways of knowing and being rather than the rigidity of the colonial systems in which they were educated is at the core of these teachers' beliefs. This also includes understanding the existing structures and ways in which they can modify curriculum and how it is delivered to better fit the needs of the students to be more engaging, relevant, and meaningful. The writing style of the article privileges the voices of Inuit educators and highlights the Inuit co-authors as education leaders in the region.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".