Research Committee: Positioning Mathematics Education Researchers to Influence Storylines
Why this work is in the frame
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Bibliographic record
Abstract
In this commentary, we identify key influences on mathematics education that are largely outside the domain of the academic world in which most mathematics education researchers live. The groups that we identify–including the media, companies and foundations, and other academic domains–affect the public's perception of mathematics and mathematics education. Identifying this set of influences in particular is important because these groups often shape policymakers' viewpoints and decisions, but there is not always agreement between mathematics education researchers and these groups about the ways in which mathematics and mathematics education are framed. Whenever a conflict is brought to the foreground, it can be difficult to raise issues without appearing defensive or sounding querulous. It is helpful, then, to bring to bear a theory that can help us interpret this reality (Mewborn, 2005); theories can provide a way to encode, read, and examine a problem as well as offer insights into the design of new practices (Silver & Herbst, 2007). In this case, we use positioning theory to examine potential conflicts between mathematics education researchers and other groups because it offers interesting interpretive insights into the phenomenon and because it can lead to potential strategies for working toward different positionings for mathematics education researchers. We begin by explaining relevant ideas from positioning theory, including storylines, positions, and communication actions. We then use these ideas to highlight current storylines underlying communication by the abovementioned groups about mathematics and mathematics education and trace some of their historical and contextual roots. We argue that mathematics education researchers can intervene to shift these storylines and positionings and to have greater impact on policy, practice, and public perception in the future. Finally, we end by offering specific suggestions for beginning this work.
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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 | 0.061 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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