Indigenous Education Policy in Canada: A Case Study of Necropolitics in First Nations Education Reform (2012–2022)
Bibliographic record
Abstract
This critical realist case study aims to examine Federal Indigenous Education Policy in Canada by exploring education reform among the member Nations of the Saskatoon Tribal Council from 2012-2022. The research questions focus on the necropolitical aspects of Crown policy, the influence of Crown policy on STC education reforms, and the “generative” mechanisms affecting the Treaty Right to Education, nationhood, and healing. The study contributes to the field of Indigenous Educational Administration and Policy by situating its analysis in the historical, political, material, and jurisdictional realities of First Nations education systems. Grounded in critical realism, the study utilizes Tribal Critical Race Theory and Necropolitics as theoretical frameworks, and employs organizational autoethnography, critical discourse analysis, legal analysis, and empirical review. The resulting data creates “laminations” which provide a layered description of federal policy and First Nations education reform during 2012-2022 and delineate how federal policy and First Nations education systems are enmeshed in material and ideational conditions which can either foster morphonecrosis (stasis) or morphogenesis (change). The findings reveal the complex dialectical interplay between federal policy and First Nations education systems, highlighting the impacts of material, structural, cultural, and agential conditions that either constrain or enable the Treaty Right to Education. The study concludes by proposing mechanisms for morphogenesis as a Positive Social Change rooted in self-determination.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.044 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".