Great Power Politics in Post-Cold War Period: The Ukraine Crisis of 2014
Bibliographic record
Abstract
The Ukraine Crisis of 2014 which led to the annexation of Crimea by Russia has been one of the worst European issues since the end of the Cold War. NATO’s relations with Russia have worsened ever since Russian troops invaded and annexed the Crimean peninsula in 2014. This paper examines why Russia intervened and eventually annexed Crimea during the Ukraine crisis through theoretical approaches in IR (international relations). In addition, the paper also discusses the consequences of Russia’s actions in Crimea during the Ukraine Crisis of 2014. This paper argues that Russia intervened and annexed Crimea during the Ukraine Crisis of 2014 because of NATO’s expansion policy in eastern Europe. The study was conducted using a qualitative and a non-positivist approach to research (interpretivist) which is centered on the humanistic view of the social sciences. On the one hand, the findings of this study support my central thesis; it revealed that NATO’s expansion policy in eastern Europe was the cause of Russia’s actions in Crimea during the Ukraine Crisis of 2014. On the other hand, the findings of this study revealed that there are alternative factors that also motivated Russia to intervene and annex Crimea from Ukraine such as nationalism, identity, and Russia’s quest for great power status. Further, Russia’s invasion and eventual annexation of Crimea without the consent of Ukrainian authorities had several consequences. For instance, it caused tension between Russia and NATO, increased military spending, and led to numerous international sanctions.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".