The phenomenon of "global education space" as an object of scientific-pedagogical research
Bibliographic record
Abstract
ABSTRACT The characteristics of global education space as a social idea of creating a system of measures to ensure the right for education to any individual as well as its converting, that is recognition regardless of the nationality and country of study; and as a specific area of human activity, which forms the internal and external environment for individual development; and as a product of a developing educational thought, the semantic side of which contains the universal interests in education, have been represented. Global education space has been defined as a part of the global social space that brings together business and education facilities within the Earth coordinates to represent the institutional forms of education and informal structures that are directly or indirectly involved in this process and, secondly, educational products (concepts, educational standards, teaching of traditional and innovative type), reflecting the goals, values, principles, content and other information about education, and examines the interaction and influence on education rights. Global education space is developed in parallel with the development of the world economy and has center-peripheral structure. To our mind, Australia, UK, Canada and the United States which we selected to make a detailed analysis in the study of trends in transnational higher education on a number of key features, belong to the “center” of global education space.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.005 | 0.055 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".