Tensions between sanctions and insolvency law: Searching for a model solution with a focus on the European Union and Poland
Bibliographic record
Abstract
Abstract This article explores the conflict between insolvency law and sanctions law, particularly in the context of European responses to Russia's invasion of Ukraine. Historically, conflicts between legal systems have shaped laws, and modern insolvency law continues this struggle by determining creditor priorities in cases where debtors cannot fully satisfy them. The article highlights how recent sanctions, which freeze assets to restrict the economic activities of sanctioned individuals and entities, complicate insolvency proceedings. The European Union, along with Poland, has imposed unprecedented sanctions on Russia, including bans on transactions, asset freezes, and trade restrictions. These sanctions, while aimed at political objectives, often push businesses into insolvency by preventing access to resources. Case studies such as GoSport in Poland, Amsterdam Trade Bank in the Netherlands, and Fortenova in Croatia demonstrate the complexities that arise when businesses linked to sanctioned entities become insolvent. Key issues include the legal treatment of frozen assets, creditor satisfaction, and the potential for sanctioned entities to benefit from bankruptcy proceedings. Poland has revised its sanctions law, introducing provisions for the appointment of independent managers to oversee sanctioned companies, ensuring continued operations without benefiting sanctioned owners. However, uncertainty remains over the management and distribution of frozen assets, with no clear framework in place. The article concludes that insolvency and sanctions law, though often in conflict, must be applied flexibly to address individual cases. A balanced approach is needed to protect creditors while adhering to the political and legal objectives of 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 | 0.001 | 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 | 0.001 |
| 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 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".