The ‘International University’ in the Age of Globalisation: A Unifier of Knowledge or an Information Factory?
Bibliographic record
Abstract
In a small, but insightful book, Civilization on Trial, written more than half a century ago, the great English historian, Arnold Toynbee, expressed great pessimism about the prospects of Western civilisation which he found to be Eurocentric (Toynbee, 1948). Toynbee's study of history was universalistic, reflecting a deep knowledge and respect for non‐Western cultures and civilisations. For Toynbee history was unified whole; it was a universal history of the entire humanity, not just of some Western people. In this sense, Toynbee is similar to the great Muslim scholar, Ibn Khaldun, the author of Muqaddimah, written almost six centuries ago, as an inquiry into the causes of the rise and decline of civilisations (Mehmet, 1990: 81–4).
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.021 | 0.039 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".