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
A complementary volume to Dilly Fung’s A Connected Curriculum for Higher Education (2017), this book explores ‘research-based education’ as applied in practice within the higher education sector. A collection of 15 chapters followed by illustrative vignettes, it showcases approaches to engaging students actively with research and enquiry across disciplines. It begins with one institution’s creative approach to research-based education – UCL’s Connected Curriculum, a conceptual framework for integrating research-based education into all taught programmes of study – and branches out to show how aspects of the framework can apply to practice across a variety of institutions in a range of national settings. The 15 chapters are provided by a diverse range of authors who all explore research-based education in their own way. Some chapters are firmly based in a subject-discipline – including art history, biochemistry, education, engineering, fashion and design, healthcare, and veterinary sciences – while others reach across geopolitical regions, such as Australia, Canada, China, England, Scotland and South Africa. The final chapter offers 12 short vignettes of practice to highlight how engaging students with research and enquiry can enrich their learning experiences, preparing them not only for more advanced academic learning, but also for professional roles in complex, rapidly changing social contexts.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| 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