The LearnHigher Resource-athon! Creative, collective contributions to the LearnHigher resource bank
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this creative, participatory workshop, colleagues had the opportunity to contribute directly to the LearnHigher resource bank. The premise was to bring together colleagues from across the sector to work together in cross-institutional teams to create new resources for LearnHigher. Colleagues benefitted from networking opportunities, as well as a chance to have their work published and disseminated online. As part of the session, participants were provided with prompts arising from the conference’s key themes – they were encouraged to consider disciplinarity/cross-disciplinary approaches, inclusivity, research-based practice and technologies for learning. The session concluded with information about the next steps in the LearnHigher resource review process and an opportunity to put any questions to members of the LearnHigher working group. Each group was supported and mentored by a member of the LearnHigher working group, who offered advice and prompts for resource development. Since the conference, colleagues have received continued support from LearnHigher mentors, as the resources are being refined, finalised and submitted for peer review, prior to publication on the LearnHigher website.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it