EXTERNAL EDUCATIONAL MIGRATION OF UKRAINIAN YOUTH: MIGRATION INTENTIONS AND FACTORS INFLUENCING THE CHOICE OF STUDYING ABROAD
Bibliographic record
Abstract
The purpose of this article is to identify young people’s migration intentions regarding obtaining education abroad and to characterize the factors infl uencing the choice of the country of study. To achieve this purpose, a sociological survey was conducted, along with general scientifi c methods (generalization, comparison, and structural-logical analysis), statistical methods, including descriptive statistics and correlation analysis, as well as graphical methods for presenting the research results. The results of a survey of pupils and students of various educational institutions in the Rivne region on their attitude towards educational migration showed that 45.2% of respondents have a desire to study abroad, 7.8% would like to, but currently do not have such opportunities, and only 33% of respondents answered that they are not interested in it. The fi ve most important factors infl uencing the choice of a country of study include: the possibility of employment after studying, the possibility of receiving a grant or scholarship to pay for education, the cost and conditions of living in the country, the amount of tuition fees and the prestige of the educational institution. At the same time, the most popular among the surveyed young Ukrainians are such specialties as economics (25%), marketing (16%) and information technologies (13%). As for the regional preferences of Ukrainian youth, the most attractive countries for studying abroad were the USA (71.3%), Great Britain (61.7%), Canada (43.5%) and Germany (33.9%). The conclusion is formulated that educational migration is extremely relevant for young Ukrainians. However, the loss of the younger generation (today about a quarter of all migrants from Ukraine are aged 18-34), which is a carrier of innovations and a driving force for development, may complicate the post-war recovery of the country. Therefore, regulating youth migration should be included in the priorities of state policy and the military economy of Ukraine. Keywords: youth, youth migration, educational migration, migration intentions, migration policy.
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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 | 0.001 |
| 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".