Equity, diversity and inclusion in management mathematics: from policy to practice, with urgency
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Accepted by: Prof. Aris Syntetos In May 2025 a panel discussion took place at the 5th Institute of Mathematics and its Applications (IMA) and Operational Research (OR) Society Conference on Mathematics of Operational Research. The panel catalysed a vital conversation on Equity, Diversity and Inclusion within management mathematics. While policies proliferate, lived experiences reveal persistent gaps: ethnic-minority researchers face lower funding odds, minoritized students encounter higher dropout rates and many initiatives risk performativity. While this editorial focuses primarily on UK-based challenges and responses, it also draws on parallel experiences from international mathematical communities—in the USA, Canada, Australia and Europe—to situate national efforts within a broader global discourse. These comparisons highlight shared structural barriers and offer transferable models of policy and practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it