Bibliographic record
Abstract
We describe mathematics classroom teaching practice in an urban Canadian prairie Cree-bilingual school using the term Cree mathematizing, which, to us, means (re)considering Euro-Western school mathematics from the perspectives of the Cree people engaging with the content. Cree mathematizing takes the form of classroom lessons in which mathematical terms are translated between English and Cree, shared through stories situated in time, place, and relationships, and contextualized by the experiences of the students and teachers. In terms of the narrative conception of identity-making, Cree mathematizing is a process of engaging in school mathematics that necessitates Cree educators and students to understand themselves as producing mathematics through their unique experiences and stories, making Cree mathematizing a partial representation of identity. We argue that Cree mathematizing is a subversive practice that challenges the ways Euro-Western school mathematics is taught as a culture-free, apolitical, and decontextualized endeavour that is devoid of human narratives of experience. Keywords: Indigenous mathematics education, Indigenization, narrative inquiry, Aboriginal education
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.034 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".