Bibliographic record
Abstract
When mathematics language is defined narrowly, emergent bilinguals in classrooms could be systematically positioned as “learners of deficiency.” Recent scholarships in the field of learning sciences call for expanding the notion of mathematics language and scrutinising learning opportunities of emergent bilinguals in relation to the history and institutional spaces. Taking a holistic and critical perspective, this study draws from Rancière’s notion of intellectual emancipation as the leverage for emergent bilinguals’ agency in mathematics learning. My study was situated in a larger project conducted in a linguistically and racially diverse school in Western Canada. Together with a teacher, the research team altered temporal-spatial structure of the mathematics classroom that can mobilize learners’ bodies in an intellectually emancipatory manner. My analysis focused on classroom discourses and emergent bilinguals’ agency in different configurations of learning environment. My findings show, in the routine session, the teacher’s intelligence and will prevailed over that of students, thus the Initiation-Response-Evaluation (IRE) or Initiation-Response-Feedback (IRF) sequences were quickly completed and the discourses alternative to the pre-set plan were discouraged. The narrow space that configured the routine session also constrained the mathematics thinking mediated by bodies to a minimal level. The teacher’s monitoring of students’ physical movements further tightened the control over learner bodies. In this learning environment, the mathematical thinking and learning tended to be compressed to unidirectional acquirement. Conversely, in the designed session, the teacher’s will and students’ intelligence took the lead. Temporal structure of classroom discourse was thinned out to the expanded intervals between teacher utterance and student utterances, and even with the absence of “evaluation” in the sequence of IRE/F. The previously restrictive area in the school was transformed to a place that augments the embodied mathematics learning. Temporally and spatially, the designed sessions were expanded and offered more uncertainty and spontaneity due to the decreased control of the teacher as an explicator. In this context, mathematics pedagogy offered a complex system of iterative adaptation and decentralized learning. Based on these findings, I discuss how integrating embodied learning and the perspective of intellectual emancipation can address equity issues in early mathematics 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| 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".