Valuing Knowledge(s) and Cultivating Confidence: Contributions of Student–Faculty Pedagogical Partnerships to Epistemic Justice
Bibliographic record
Abstract
Abstract This chapter draws on data from two studies, one in Canada and another in the United States, focused on the experiences of pedagogical partnership as described by students traditionally underrepresented and underserved in higher education. These students argue that such collaborations with faculty hold promise for creating more inclusive and responsive practices. Using the concept of epistemic justice, the authors explore how partnerships can facilitate epistemological forms of equity and inclusion by (1) creating more equitable conceptions of knowing and knowledge that open possibilities for (2) fostering students’ confidence in their knowledge and willingness to share it with others. The authors argue that partnerships – in their epistemic, relational, and affective impacts – are one powerful way to recognize underrepresented and underserved students as “holders and creators of knowledge” (Delgado-Bernal, 2002, p. 106) and bring about greater epistemic justice in higher education.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".