The long way home: Migration trends of Ukrainian researchers in the modern world (1991‒2023)
Why this work is in the frame
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Bibliographic record
Abstract
In a modern world marked by intense migration processes, the analysis of the migration of Ukrainian scientists and their choice of destination countries, especially in the context of recent events in Ukraine, is an important subject of scientific research. This study examines migration trends among Ukrainian researchers in various historical periods from the early 1990s to the present. The research is based on the analysis of scientific literature for theoretical insights and previous studies, the use of statistical data from the State Statistics Service of Ukraine, the analysis of political, economic, and sociocultural contexts to understand migration factors, methods of observing real events and processes, and historical analysis to trace the evolution of migration processes. Factors influencing scientists' decisions regarding migration and their motivations, as well as destination countries, were analyzed in the article. Three key migration stages are highlighted: the post-Soviet period (1991–2012), the post-revolutionary period (2013–2021), and the period of full-scale war (2022 and onwards). The first stage, covering the years 1991–2012, was characterized by the outflow of scientists in search of economic opportunities and stability. Destination countries during this stage included the USA, Russia, Germany, Israel, Canada, and Poland. The second stage, from 2013 to 2021, was marked by deep social and political transformations in Ukraine following the Euromaidan Revolution and the annexation of Crimea by Russia. Scientists chose Germany, Canada, and Poland for academic collaboration and research funding.The third stage, which began in 2022 and continues to the present, is defined by the full-scale war in Ukraine. Scientists are leaving the country due to a sense of danger and military conflict. The primary migration destinations are EU countries, which offer opportunities for academic cooperation and safety. Prospects for further scientific research lie in the analysis of the historical roots of the migration of Ukrainian scientists, including the impact of events and reforms in Ukraine and the world on migration processes.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it