COMPETITIVENESS OF HIGHER EDUCATION SYSTEM: INTERNATIONAL DIMENSION
Bibliographic record
Abstract
The globalization of the scientific-educational area determines the search for new competitive advantages of universities. One of the modern instruments of competition in the world educational services market is universities ranking. Nowadays the educational rankings are widespread; they are studied by researchers and experts of international organizations. In the same time the high dynamism of scientificeducational area requires the permanent monitoring of the competitive positions of the national higher education systems. The purpose of the article is to analyze the competitive positions of higher education systems of selected countries in the world rankings, as well as to identify the directions of increasing their competitiveness in the context of globalization and digitization of the scientific-educational area. The authors studied the methodology of a range of popular rankings of educational systems, and analyzed the ranks of selected countries (United States of America, Switzerland, United Kingdom, Sweden, Denmark, Canada, Finland, Norway, Ukraine, Germany, France, Austria, Poland, China, and Spain). The selection is based on the differentiation of the countries according to the geographic position and ranking position. The source of data: bases of international organizations OECD, World Bank, UNESCO, ILO; and rankings ARWU, SCImago, Webometrics, and Leiden Ranking. Based on the comparative analysis, the article concludes that the increasing of competitiveness of the national higher education system needs the use of integrated approach combining the set of educational, research, financial, internationalization, and managerial components. The authors emphasized the urgency of developing and implementing institutional strategies for internationalization of universities, synchronized with national ones.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".