МУЛЬТИКУЛЬТУРАЛІЗМ ТА ЙОГО ВПЛИВ НА ОСВІТУ
Bibliographic record
Abstract
The article considers the problems of multiculturalism, which are primarily related to socio-economic and political inequalities and misunderstandings between people of different cultural backgrounds and ethnic backgrounds. The cultural diversity of modern society provides the basis for a heightened imperative to develop multicultural education as an education that should help to live together in multicultural societies. Multicultural education, which began its development more than half a century ago in the USA, Canada, Australia, and now is dynamically developing today and in many Western European countries. On the territory of the European educational space, the multicultural dimension of higher education has become particularly important over the last decade, owing to the cultural diversity of European countries, owing to the openness of borders and the critical increase of immigrants, to which national authorities in European countries have responded with new legal and educational institutions. In view of the stated above, research into the development of multicultural education is important, based on the theoretical developments of educators and scholars, and on the best practices of educational institutions of the leading countries in the world, which are actively implementing this strategy. The author proposes to focus on the multicultural dimensions of education strategies as one of the key cultural and humanitarian education development strategies in the context of dynamic social transformations and globalization processes. In conclusion, the author emphasizes that the educational policy of many countries of the world pays much attention to multicultural education in order to improve social cohesion, reduce social exclusion, inequality, and to develop human capital, as well as defines the perspectives of development of multicultural education in Ukraine.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.012 |
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".