The "Verbification" of Mathematics: Using the Grammatical Structures of Mi'kmaq to Support Student Learning.
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Bibliographic record
Abstract
Miss, you're talking crazy again! My students would sometimes say this to me dming the ten years I taught secondary mathematics in a Mi'kmaw [l] community school in Cape Breton, Nova Scotia. The accusation ofcrazy talk was always an indication that I needed to repluase my explanations and find new words, new ways, to help students make sense of a concept like most indigenous languages in Canada, Mi'kmaq is a verb-based language Over the years, the accusations of crazy lessened as I shifted my way of explaining concepts to be more consistent with the verbbased linguistic strnctures ofMi'kmaq even though I was teaching in English In this article, [2] I will share one aspect of a larger research project focused on transforming mathematics education for Mi'kmaw students In particular, I will describe the concept of ver bification as a linguistic process that stands in contrast to the predominance of nominalisation in the teaching and learning of mathematics. I will argue that ver bification holds promise as a means of supporting Aboriginal students in mathematics learning
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it