Student pedagogical partnerships to advance inclusive teaching during the COVID-19 pandemic
Bibliographic record
Abstract
The current health crisis brought about by the COVID-19 pandemic not only had a global impact, it also exacerbated the inequalities experienced by students of diverse backgrounds in the United States. Implementing inclusive and anti-racist pedagogical practices has gained a heightened and overdue sense of urgency, especially during the period of emergency remote teaching. At Lafayette College, a small liberal arts college in Pennsylvania, USA, the Inclusive Instructors Academy is a semester-long program aimed at supporting faculty from all disciplines to develop and incorporate inclusive practices that promote equity and belonging in their teaching. A critical aspect of the Inclusive Instructors Academy is its employment of student fellows under the Student-as-Partners model. The student fellows who participated in Fall 2020 and Spring 2021 provided feedback to their faculty partners on inclusive teaching approaches. This case study highlights how student-faculty partnerships can be a highly effective strategy for fostering more socially just learning environments.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.003 | 0.038 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".