The Variation of Universally Acknowledged World-Class Universities (UAWCUs) between 2010 and 2015: An Empirical Study by the Ranks of THEs, QS and ARWU
Bibliographic record
Abstract
Due to certainty recognition in ranking systems, the commonly included top 100 universities are regarded as the Universally Acknowledged World-Class Universities (UAWCUs). From three university rankings-THEs, QS and ARWU from 2010 to 2015, the following conclusions can be drawn from this study: Firstly, 56 universities are commonly ranked in the top 100 by THEs, QS and ARWU in 2015, comparing with that of 47 in 2010; Secondly, comparison between 2010 and 2015 reveals that 44 of these higher ranked UAWCUs have kept on the group of top 100 universities in any ranking system. However, three lower ranked UAWCUs in 2010 have dropped out the group of top 100 universities in 2015, which are replaced by some progressed universities; Thirdly, both US and UK have nearly 3/4 and 2/3 of these UAWCUs in 2010 and 2015, respectively; Lastly, this paper denotes that consistently strives to build on its strong reputation for research excellence, consistently pursuing innovative research, delivering excellence in teaching through internationalization, obtaining support from the government would be the critical factors to promote UAWCUs to improve their performance and rankings.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".