Social Identities and Opportunities to Learn: Student Perspectives on Group Work in an Urban Mathematics Classroom
Bibliographic record
Abstract
In this article, the authors investigate group work in a heterogeneous urban high school mathematics classroom. Two questions are explored: How do students describe cooperative group work in their mathematics class? How do students describe the way their socially constructed identities influence the nature of their group interactions in mathematics classrooms? The authors present a case study of the ways in which race, gender, and other social identities might influence the nature of group work in reform-oriented high school mathematics classrooms. The analysis, based on 14 interviews with high school students, focused on students’ perceptions of group work and their theories about when cooperative groups work well and when they do not. Students named interactional style, mathematical understanding, and friendships and relationships as the most influential factors. Using an analytic lens informed, in part, by critical race theory, the authors highlight the racialized and gendered nature of these factors.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.023 | 0.019 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".