Becoming Nikanaittuq - Strengthening the Indigenous-Based Teaching Practices of non-Indigenous Educators
Bibliographic record
Abstract
In 2015, The Truth and Reconciliation Commission (TRC) of Canada published its 94 Calls to Action to address the atrocities that Indigenous people have experienced since first contact with Europeans and laid the groundwork for the reconciliation process between Indigenous and non-Indigenous people. The report makes particular references to educational reform being essential if reconciliation is to be successful. At present, many non-Indigenous educators at Snowy Mountain Academy (SMA, a pseudonym) hold a predominantly colonized and Eurocentric educational philosophy resulting in the lack of a culturally relevant educational program which has negatively impacted the sense of identity, culture, and belonging of Indigenous students. The Problem of Practice (PoP) to be addressed in this Organizational Improvement Plan (OIP) is the need to implement initiatives focusing on building the pedagogical understanding and self-efficacy of non-Indigenous educators, improving their ability, confidence, and willingness to educate all students on the cultures, traditions, and worldviews of Indigenous peoples. As an adaptive, authentic and culturally responsive educational leader who is envisioning this PoP using a social constructivist and two-eyed seeing lens, I will work in collaboration with educational stakeholders to develop and guide the implementation of strategies that enable non-Indigenous educators to integrate Indigenous-based perspectives into their teaching practices. This integration is done to recognize and validate the important contributions of Indigenous peoples in the formation of modern-day Canada and to empower Indigenous and non-Indigenous students with the knowledge of the important contributions Indigenous peoples make to shaping Canada as a country.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".