Co-selecting students for more democratic co-creation: A case study from the Create a Subject Challenge
Bibliographic record
Abstract
Democratic processes are at the foundation of the students-as-partners (SaP) framework. Student selection for SaP projects however, is typically in the hands of staff, which is undemocratic and faculty assumptions and practice exclude particular students from co-creation projects. We describe a case study in which students and staff jointly select students for a co-creation project in the School of Biomedical Sciences at the University of Melbourne. Our reflections suggest that co-selection, compared to selection of students by staff alone, further realizes the democratic ideal of SaP by integrating the student perspective early in the co-creation process. We reflect on the democratic processes in our case study through the lens of deliberative democracy and share prospects and perils of voting and deliberation to embed the student voice in student selection for co-creation.
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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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.014 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".