Towards a Conscious Integration of EDI Values on Canadian Campuses: A Case Study Analysis
Bibliographic record
Abstract
Campuses are focusing on Equity, Diversity and Inclusion (EDI) initiatives and programs as a response to urgent calls for higher education institutions to exemplify these principles. This study focused on determining the current environment for embedding EDI principles to identify next steps in galvanizing efforts in this work. This qualitative multi-case study had two phases. In the first phase, we conducted an environmental scan of the websites of the 15 research-intensive universities in Canada (U15) to determine how EDI efforts were included in any publicly available documents and on the websites. In the second phase, we conducted semi-structured interviews with members of an EDI Champions committee at one campus to explore how the EDI commitments were being actualized on that campus. Participants confirmed that work was ongoing but that determining a shared understanding of EDI, articulating a strategy for implementation, and promoting EDI efforts on campus faced many challenges including creating understanding and commitment across campus to further the EDI strategies. Campuses need a well-articulated strategy complete with processes and targets to inform campus members about EDI, determine ways to support action, and articulate ways to measure progress against EDI goals.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".