(Re)Imagining higher education: an inspirational guide for academics
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
We live in times of certain uncertainty with Higher Education in constant need of reflexive adaptation. The Reimagining Higher Education project, funded by the Association for Learning Development in Higher Education (ALDinHE), explored creatively and playfully the future of education. It invited the academic community to participate in workshops to reflect on the current status of Higher Education and, at the same time, to conceptualise what form a humane and integrated Learning Development, the holistic and sustainable fostering of academic literacies and practices, would take within that Higher Education system. The outcome is an open-source guide of Higher Education models, real and idealised, that potentially have the power to change perspectives and attitudes. In this short presentation, we (the project team) will showcase the guide, outlining what a more inclusive, empowering, and creative academia would look like. Our research participants have imaged the unimaginable: universities open, accessible, full of trust, care and laughter. Please join us to further reflect on the future of academia, with hope and positivity.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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