Estimating the impact of the Russian invasion on the displacement of graduating high school students in Ukraine
Bibliographic record
Abstract
Abstract On 24 February 2022, Russia began a full-scale invasion of Ukraine. The war has dramatically impacted every area of life in Ukraine, including education. In this paper, we curate a uniquely comprehensive dataset of standardized exam outcomes used for admissions to higher education institutions in Ukraine—analogous to the Standardized Aptitude Test (SAT) in the United States—to provide strong estimates of student displacement and the first analysis of student drop-off , or decline of participation in the Ukrainian education system, following the Russian full-scale invasion. We conducted descriptive statistical analysis, which included computing and comparing means across groups of students, conditioned on geographic location, migration pattern, and demographics, coupled with data visualization. We found that, among the graduating Ukrainian high school students in 2022, approximately 36,500 (16%) were displaced, with 64% of them moving abroad, primarily to Poland, Germany, and Czechia. Most displaced students originated from the front-line war regions, and either moved abroad or migrated towards the central and western parts of Ukraine. Further, we found a 21% decline in graduating high school students taking the standardized higher education entrance exam in 2022, as compared to 2021. This drop-off from the common educational pathway consists of approximately 41,500 students. With these findings taken together, we estimate that at least 78,000—a staggering 34%—of high school seniors have been directly impacted by the Russian invasion of Ukraine. We also study the impacts on subgroups and at the intersection of socio-economic status (as measured by urban vs. rural location) and gender, and find that intersectionality exacerbates the impacts, with men from rural areas being particularly adversely impacted. We conclude this article by reflecting on several policies pursued by the Ukrainian government and its institutions, aimed at minimizing disruptions to the school year and retaining students. Our analysis has important implications for governmental organizations like the Ukrainian government and the European Union, and human rights organizations like the UN Refugee Agency and the International Organization for Migration who wish to understand the impact of the Russian invasion on the education system in Ukraine.
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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 | 0.002 | 0.001 |
| 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".