The Politics of Mathematics: Just and Knowing Societies
Bibliographic record
Abstract
Educational leaders and researchers recognize that mathematics can be an effective tool in enabling substantial advances in many fields of science and technology. However, the role that mathematics can play in shaping and creating socio-political views of societies is not as well understood. Within the mathematics’ learning community there is little discussion connecting the unique role that mathematics can play in conceptualizing a democratic society even within the democratic societies where that learning happens. Building capacity for learning in context is a critical piece of any comprehensive program but it is sometimes difficult for leaders to agree on what that context should and does look like. There are multitudes of influences at play when educational systems create and enact curricula but in order to push through the stalemate that can exist with different ideologies, it is essential to understand that mathematics can be a conduit to improvements in political social justice as well as a gateway to developments in science and technology. Mathematics has the potential to be a tool to create, as well as an instrument of influence; the key is for leaders to understand how to do both.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.038 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".