Development of an Equity, Diversity, and Inclusion Curriculum Initiative for Undergraduate STEM Students
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
Equity, diversity, and inclusion (EDI) gaps persist in science, technology, engineering, and math (STEM) fields, as demonstrated by the discrimination, stereotyping, and inequities that historically and persistently marginalized groups face. Recognition of this gap led a transdisciplinary team to develop foundational-level e-learning modules, titled Foundations for Inclusive and Respectful Engagement (FIRE) on EDI capacities to be delivered in STEM undergraduate classes at the University of British Columbia’s Okanagan campus. FIRE consists of online, asynchronous, self-study modules delivered through the learning management system, Canvas. Feedback from pilot testing the FIRE modules has demonstrated that STEM students find the modules to be relevant and beneficial. Throughout the development of FIRE, we learned the importance of aligning the course with our institution’s values, working in a transdisciplinary team, and revising iteratively. This documentation of the development and preliminary feasibility of the FIRE modules aims to assist other institutions or organizations who are in the process of developing their own EDI teaching and learning materials.
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 | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| 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