Areas of social impact of top-listed universities worldwide
Bibliographic record
Abstract
This chapter aims to introduce the key areas of universities’ social impact out of the Times Higher Education Impact Rankings (THE Impact Ranking). To reach the aim, we adopted detailed research questions: (1) Is there a leading university that has maintained a high position since it first appeared in the ranking? (2) In which countries are the top 10 universities located? (3) Which goals are least often indicated by the top 10 universities? (4) In which Sustainable Development Goals (SDGs) did the top 10 universities achieve the highest score? We analyze the top 10 universities, starting from 2020. In the ranking, the universities’ impact is assessed by its achievements in SDGs. The chapter is analytical. The authors carried out a critical analysis of the literature on the subject and presented the findings, which indicate a steady increase in the number of universities from different regions of the world that are pursuing selected SDGs in their activities. The top 10 list in the THE Impact Ranking is dominated by universities from Australia and Canada. Certain goals – no. 2 (zero hunger), no. 1 (no poverty), no. 14 (life below water), and no. 7 (affordable and clean energy) were least often indicated by the top 10 universities.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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 teacher head, 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".