Empowering student partners
Bibliographic record
Abstract
This case study reflects on a project that utilised student-staff partnerships to explore how best to prepare staff for collaboration in such partnerships. Eight student researchers worked together across four higher education institutions in the United Kingdom, conducting interviews with 41 participants, including both staff and students. The partnerships studied at these institutions, represents a mix of research-intensive and teaching-focused universities, covering a wide range of academic disciplines. The project examined experiences and the values of partnership, offering practical insights to support the development of successful student-staff collaborations. This student-led initiative summarises key findings, such as how narrative interviews facilitated an understanding of partnership values. It presents a practical resource toolkit to support institutions engaging in partnership work. Collaborative efforts were crucial in exploring power dynamics and trust within the project. The reflections in this case study will be valuable for students, educators, researchers, and others interested in developing student-staff partnership projects.
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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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.002 | 0.035 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".