MétaCan
Menu
Back to cohort
Record W4414646337 · doi:10.1007/978-3-031-98724-3_8

The Origins of the Russia-Ukraine War

2025· book-chapter· en· W4414646337 on OpenAlexaff
Ivan Katchanovski

Bibliographic record

VenueRethinking political violence · 2025
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean and Russian Geopolitical Military Strategies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAnnexationAllianceAccessionSpanish Civil WarGovernment (linguistics)State (computer science)

Abstract

fetched live from OpenAlex

Abstract This chapter examines the origins of the Russia-Ukraine war. It analyzes narratives of the causes of this war by the Ukrainian, Russian, and Western governments and the media. It examines the role of such factors as the NATO accession of Ukraine, Russian imperialism, the Maidan, democracy, and the far right in the start of the war. The analysis shows that the illegal Russian invasion of Ukraine on February 24, 2022, represented the extreme escalation by Russia of the conflicts with Ukraine and the West, the civil war in Donbas, the annexation of Crimea, and the Western-backed violent and illegal overthrow of the pro-Russian government in Ukraine by the oligarchic and far-right alliance by means of the Maidan massacre and assassination attempts during Euromaidan. NATO accession of Ukraine was a major factor, but it, like the role of the far right, was inflated by Russia. Russian imperialism was also significant but secondary factor. Ukraine is not a democracy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.007
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0040.001
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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

Explore more

Same venueRethinking political violenceSame topicEuropean and Russian Geopolitical Military StrategiesFrench-language works237,207