Curriculum Integration and the Forgotten Indigenous Students: Reflecting on Métis Teachers’ Experience
Bibliographic record
Abstract
Curriculum integration, or in other words, changing what students are taught within racially desegregated Canadian schools, has served as a primary but incomplete pathway to racial justice. In this paper, I present evidence from a qualitative critical race theory (CRT) methodological study with 13 Métis teachers to demonstrate how curricular integration has been framed as a key solution to inequitable outcomes concerning Indigenous students. This strategy has been instilled within the Saskatchewan K–12 education system by a wide spectrum of authorities over several decades. Although absolutely essential for multiple reasons, I argue that teaching students about Indigenous knowledge systems and experiences, as well as anti-racist content, cannot resolve the systemic racial injustices encountered by Indigenous students who attend provincial schools. In particular, three CRT analytical tools—structural determinism, anti-essentialism, and interest convergence—are utilized to examine the limitations of curricular integration as a strategy of racial justice. Keywords: Métis teachers; Indigenous education; critical race theory; integrated 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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.026 | 0.019 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".