Russia’s Invasion of Ukraine: Accounting for the Domestic alongside the International
Bibliographic record
Abstract
Abstract An old debate on the value of systemic explanations of international relations (IR) reemerged in the wake of Russia’s full-scale invasion of Ukraine. Both scholars and popular media have spent much oxygen and ink debating arguments that assign causal primacy to NATO expansion, status reclamation, spheres of influence, dissatisfaction, or multipolarity. However, understanding conflict onset and duration requires consideration of both domestic and international causes. Though accounting for both has been relatively sparse in the public discourse of Russia’s invasion, efforts to engage both have a long history in IR scholarship. This forum addresses this omission in the Russia–Ukraine War, outlining the problems with the dominant systemically focused narrative while offering suggestions for more fruitful avenues rooted in both IR and area studies. Doing so offers a more thorough accounting of the war and emphasizes the broader interdependence between IR and area studies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".