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Record W2509736026 · doi:10.1111/jcms.12447

Ukraine between a Constrained EU and Assertive Russia

2016· article· en· W2509736026 on OpenAlexaff
Taras Kuzio

Bibliographic record

VenueJCMS Journal of Common Market Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicPost-Soviet Geopolitical Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsXenophobiaUkrainianNationalismPolitical scienceIndependence (probability theory)AssertivenessPolitical economyPower (physics)Development economicsSociologyImmigrationLawPoliticsEconomicsPsychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract The article analyzes three factors constraining EU power: its unwillingness to view Ukraine as a candidate for membership, a miscalculation of Ukrainian leaders and the ignoring of growing nationalism and xenophobia in Russia. These three factors constrained the EU in its ability to respond to the Russia–Ukraine crisis by ignoring past Russian support for separatist movements and invasion of Georgia and recognition of the independence of two separatist enclaves. The EU did not appreciate that Russia also viewed the EU (not just NATO) as a hostile actor intervening in what it views as its ‘zone of privileged interests’.

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)0.002
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.010
Scholarly communication0.0050.002
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.042
GPT teacher head0.383
Teacher spread0.341 · 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
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

Citations66
Published2016
Admission routes1
Has abstractyes

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