Radical Reconfiguring(s) for Equity in Urban Mathematics Classrooms: Lines of Flight in <i>Mathematics and the Body: Material Entanglements in the Classroom</i>
Bibliographic record
Abstract
n Mathematics and the Body: Material Entanglements in the Classroom by Elizabeth de Freitas and Nathalie Sinclair (2014), the authors call for a "radical reconfiguring" (p.225) of mathematics education.Similarly, Barad (2012) argues that "theories are living and breathing reconfigurings of the world" (p.207) and that putting new materialist and posthumanist theories to work in mathematics education could open up a space for this radical reconfiguring.This book review is based on our developing thinking about the use of theory and its possibilities within urban mathematics education.We situate ourselves in what de Freitas and Sinclair call a "stretchy space of continuous transformation" (pp.90-91)-continuing to think and re-think issues like equity with this text, letting the words wash over us (St. Pierre, 2003), opening up and questioning urban mathematics education research.As two White women mathematics educators and emerging scholars in the field, we do not assert that theory alone or theory removed from practice can address the complex, prevalent, and long-lasting inequities present in mathematics education; however, we view theory in concert with practice as having potential to advance the field.de Freitas and Sinclair's theories, which they use to question school mathematics in general, could be built upon and deployed to expose the problematic presence of White rationality (Martin, 2015) in urban classrooms.We encourage the reader to join us in this stretchy space and embrace the potentialities of the book as an as-1 de Freitas, E., & Sinclair, N. (2014).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| 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".