Economic effects of isolating Russia from international trade due to its ‘special military operation’ in Ukraine
Why this work is in the frame
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Bibliographic record
Abstract
The international community has reacted with surprising speed and unity to Russia’s ‘special military operation’ on Ukrainian territory through commercial and financial sanctions to achieve its economic isolation. This military action will change the relations between Russia and most world countries in ways that cannot yet be foreseen. This study analyzes the short-term effects of international trade interruptions on the economy, considering different isolation scenarios. The hypothetical extraction method and a multi-regional input-output model are used to simulate the economic effects on the production of 189 countries. The results show that the most affected country is Russia, with a drop in production of 10.1% in the scenario with sanctions from the European Union and 14.8% when the sanctions are also applied by Australia, Canada, Japan, United States, and the United Kingdom. The European countries with the greatest geographical proximity and strong trade flow with Russia suffer a significant drop in their production, including Lithuania, Latvia, Estonia, Finland, Hungary, and Poland. In Russia, the most affected economic sectors are Re-export & Re-import and Mining & Quarrying. Finally, the estimated impacts are a lower bound since the effects associated with financial sanctions, exchange rates, commodity prices, among others, are not considered.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it