Exploring Language in Bilingual and Multilingual Mathematics Classrooms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, I explore ways in which language and mathematics may be used, perceived and learned in bilingual/multilingual mathematics classrooms. I propose a social view of mathematics that considers language, and in particular language in interaction, to be a crucial part of all mathematics classrooms, especially in bi/multilingual contexts. To begin, I reflect on the nature of the relationship between language and mathematics. In order to do so, I draw on key ideas from sociocultural theories of second language education and mathematics education, and from seminal research regarding the mathematics register. Focusing on the unique context of bi/multilingual mathematics classrooms extends the discussion. I conclude with suggestions for ways in which researchers and educators working in various bi/multilingual contexts can adopt a broadened view of mathematical discourse.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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