The Development of Higher Education Research in Europe
Bibliographic record
Abstract
Though the book is a contribution to celebrate the 25th anniversary of the Consortium of Higher Education Researchers (CHER), it is not just about the history of the organisation as such. The contributions provide an account of the emergence of higher education as a field of study and research in Europe, its institutionalisation, and its relationships to higher education policy and practice. Furthermore, higher education research in Europe is contrasted to and contextualised by the example of higher education research and scholarship in Australia. The book is useful as an account about the emergence and development of higher education research as a field of study and research in Europe. It will be an interesting and insightful read for all scholars and young researchers wanting to know about higher education research but also for scholars in fields like history of science, disciplinary differentiation, institutionalisation of fields of knowledge and research.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.018 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".