Social communications of students in the modern intercultural space
Bibliographic record
Abstract
The aim of this article is to study the influence of social communications on the formation of relations between students in the intercultural space on the example of the State Higher Educational Institution "Vasyl Stefanyk Precarpathian National University" and Kyiv University named after Borys Hrinchenko. Methods: analysis, synthesis, abstraction, modeling, description, observation, comparison, tabular and graphical representation, questionnaires and generalizations. Results: It is determined that countries such as Australia, Canada, Great Britain, New Zealand, France and the Netherlands have the highest rates of attracting foreign students to study in higher education institutions. The most international universities in the world are the University of Hong Kong, ETH Zurich, Chinese University of Hong Kong, University of Oxford and Imperial College London, which occupy the first five positions in the World University Rankings 2021. It was found that most often social communication between students belonging to different socio-cultural groups occurs using social media.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".