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Record W4407834407 · doi:10.1080/13518046.2025.2463169

‘It’s Our War as well’: Belarusian Fighters in Ukraine (2014-2023)

2025· article· en· W4407834407 on OpenAlexaff
Katsiaryna Lozka, David R. Marples

Bibliographic record

VenueThe Journal of Slavic Military Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEastern European Communism and Reforms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPolitical scienceAeronauticsEngineering

Abstract

fetched live from OpenAlex

The presence of foreign fighters in wars has been a factor in many countries. Foreign fighters from Belarus have played important roles in the war in Ukraine that started in 2014 and was expanded with the full-scale Russian invasion of February 2022. This article explores the motives of those who fought on both sides, and the backgrounds of some of the leading participants. It demonstrates how the uprising in Belarus that followed the flawed presidential elections of 2020 served as a catalyst for a growing number of Belarusians who perceived Ukraine’s cause as a means to bring about regime change in Belarus and end the long-time leadership of Aliaksandr Lukashenka. It explores the motives of the participants in the war, indicating that while some seek the experience of using modern weapons in a military conflict, others are swayed by official propaganda, and still others fight for ideological reasons, often because of a political crisis in their homeland, hoping that a victorious war in one country might catalyze change and bring new leaders to their own. The fact that Belarusians can be found on both sides of the fighting illustrates the divided viewpoints across the country toward the Russian invasion of Ukraine and Russia’s ‘Special Military Operation’. A large majority of Belarusians, however, are opposed to the national army being deployed to Ukraine and thus far the Lukashenka regime has avoided such involvement.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.344
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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