REDI or Not? The Experiences of Equity-Deserving Students in the Wake of Massification and Widening Participation
Bibliographic record
Abstract
It can be argued that while post-secondary institutions in Canada are actively engaged in reconciliation, equity, diversity, and inclusion (REDI) efforts, the evidence regarding how or if these initiatives are being incorporated into student support services is lacking. The shift from elite to mass to universal access in higher education has been a primary catalyst for increased access and the diversification of the student body. While this expansion has been beneficial, the administrative and support systems required to accommodate these changes have not evolved at the same rate. This has resulted in a number of challenges for student support services that impact students’ ability to get the supports they need, and in a timely fashion.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.032 |
| Scholarly communication | 0.018 | 0.010 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".