Exploring representation (EDI) in Students as Partners (SaP) initiatives: a case study of equity, diversity and inclusion in the Students as Partners Program (SaPP) at Carleton University
Bibliographic record
Abstract
Students as Partners (SaP) initiatives have been gaining traction in the past decade, and many institutions are praising the SaP model as a method to enhance collaborative, reciprocal, and equitable learning. In this paper, we offer insights on student and faculty experiences of the Students as Partners Program (SaPP) at Carleton University in Ottawa, Canada. Our research is motivated by the question: to what extent are Students as Partners Programs (SaPP) compatible with goals of equity, diversity and inclusion? We take a qualitative, case study approach to explore student (n = 51), and faculty (n = 67), experiences of the Students as Partners Program in 2020. Our findings reveal strong participation by students with a disability, and female, and BIPOC students, and an overrepresentation of white, able-bodied participants at the faculty level. To improve EDI in SaP initiatives, we share recommendations from student and faculty participation.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.018 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".