Features of Adaptation of Ukrainian Refugees in the EU, Great Britain, USA, and Canada
Bibliographic record
Abstract
Russia's armed aggression against Ukraine has resulted in tens of thousands of deaths, destruction of cities and towns, homes and infrastructure. The constant threat is a consequence of the large flow of refugees who are forced to leave the country in search of security and asylum. European Union countries, the United Kingdom, the United States, and Canada have accepted those fleeing the war and provided temporary protection. The relevance of the study consists in the identification of ways for assistance and benefits conferred, which are aimed at adapting and supporting Ukrainian refugees. The purpose of this paper is to study the features of adaptation of Ukrainian refugees in the EU, Great Britain, USA, and Canada, the socio-psychological state of refugees during the adaptation period, to compare the concepts of “refugee” and “person in need of temporary protection”, the characteristics of the social assistance package for Ukrainian refugees. The methods used to investigate the topic are: comparative, legal recognition, logical and legal method, hermeneutical method, analysis, etc. The results of this study are a comparison of the main concepts, including: “refugee”, “person in need of temporary protection”, characteristics of Ukrainian and international laws and regulations on refugee protection issues, clarification of the features of adaptation of Ukrainian refugees in the EU countries, Great Britain, USA, and Canada, psychological aspects of refugee adaptation, comparative analysis of social assistance and benefits for refugees between EU countries, Great Britain, USA, and Canada, processing statistics to compare the number of refugees between countries that provide asylum and protection. The provisions presented in this paper reveal the current problems of adaptation of Ukrainian refugees in the EU, Great Britain, USA, and Canada and may be useful for further study
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".