Accessibility, authenticity, and agility
Bibliographic record
Abstract
Student loneliness is a prevalent challenge across universities around the globe. Epistemological, ethical, and efficacious challenges characterise contemporary research on student loneliness. To address this, our team of 11 staff researchers implemented a students-as-partners initiative with 16 students from 12 universities across the United Kingdom (UK). This student research team were responsible for co-producing the design, delivery, and dissemination of a research project to understand student belonging and loneliness. Adopting a participatory evaluation approach co-authored with seven members of the student research team, this paper critically examines strengths and limitations in our team’s approach to addressing common challenges in student-as-partners activities, namely engaging underrepresented groups, fostering meaningful and authentic engagement, and navigating sensitive topics. In doing so, we elicit good practice for inclusive, accessible, and impactful research with students as partners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.001 | 0.020 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".