Responding to the challenges of student-staff partnership: the reflections of participants at an international summer institute
Bibliographic record
Abstract
This article contributes to the growing scholarly literature about students as partners in learning and teaching in higher education by describing an initiative designed to support partnership and a study investigating international staff and student perspectives. The initiative – an international summer institute – is a four-day, professional development experience that brought together students and staff from seven countries to learn about partnership and develop specific partnership projects. Participants in the institute were invited to contribute to a qualitative study exploring their experiences of students as partners work and their perceptions of the institute’s capacity to support it. Given that much existing research on this topic tends to be celebratory, we focus here on the challenges participants ascribed to student-staff partnership, and on the features of the summer institute they thought particularly useful in helping them to navigate these difficulties. Looking beyond the summer institute, we consider the implications of these findings for those looking to support partnership more broadly.
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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 | 0.025 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.036 | 0.023 |
| Scholarly communication | 0.016 | 0.009 |
| Open science | 0.005 | 0.023 |
| Research integrity | 0.009 | 0.021 |
| Insufficient payload (model declined to judge) | 0.004 | 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".