Professional learning for culturally nourishing pedagogies in Inuit schools
Bibliographic record
Abstract
This article presents a participatory action inquiry into the process and outcomes of professional learning for culturally nourishing pedagogies in Inuit schools. Culturally nourishing pedagogies are approaches to schooling that centre local knowledge, language, culture, and knowledge holders. Engaging all school staff, administrators, curriculum developers, and school boards in adopting such approaches is key to decolonizing schools and practicing Indigenous sovereignty in education. A research team of Inuit educators and university-based researchers, in partnership with the Nunatsiavut Inuit Government and the school board documented and analyzed the development, delivery, immediate and short-term outcomes of professional learning workshops addressing Inuit culturally nourishing pedagogies. Results show that the teachers have many ideas for, and intuitively incorporate land, language, local knowledge holders, and local resources in their teaching inside and outside the school building. Consistent implementation of culturally nourishing pedagogies is hindered by capacity, time, school board policies, and resource gaps. Teacher-to-teacher knowledge exchange in the workshops demonstrated the importance of identity, relationship, and safe spaces in generating ideas for and practicing culturally nourishing pedagogies. Collaborative co-creation of knowledge reveals how professional learning workshops can contribute to teachers’ effective practice and to sustainable change in Nunatsiavut area schools.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".