Tools for transformation: a teaching toolkit and research pocket guide for advancing equity, diversity, and inclusion in science and engineering
Bibliographic record
Abstract
Advancing equity, diversity, and inclusion (EDI) in scientific fields is an outstanding challenge. While there is growing awareness of barriers and challenges to EDI across science, technology, engineering, and mathematics (STEM), individuals may lack the knowledge and/or skills to effect change. This Perspective article describes two resources we developed: (1) a Teaching Toolkit, entitled “Science is for everyone: Integrating equity, diversity, and inclusion in teaching science and engineering—a toolkit for instructors”, and (2) a Research Pocket Guide, entitled “Striving for inclusive excellence in science and engineering research: a pocket guide”. The Teaching Toolkit offers actions, activities, and tools specifically designed for instructors to implement in STEM courses. The Research Pocket Guide offers a dynamic reference tool that is useful to a broad range of researchers. Both resources are distributed under creative commons license and may be adapted for different institutions and contexts. The Teaching Toolkit and Research Pocket Guide are unique with their combination of colourful graphics and novel collections of actionable steps to engage with EDI concepts both in classrooms and research teams. It is our hope that these resources will catalyze change towards advancing EDI in STEM.
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.
How this classification was reachedexpand
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.007 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".