Ensuring the Fulfillment of Contracts in Civil Law
Bibliographic record
Abstract
The main purpose of the article is to comprehensively describe the main ways to ensure compliance. The main research approach is analytical and legal methodology. Doctrinal and legislative provisions on ensuring the implementation of civil law agreements were analysed. The process of formation of the institute ensuring the fulfilment of contracts was characterised. A comparative analysis of ways to ensure the implementation of agreements on their legal nature and effectiveness, highlighted the signs of their demarcation. The foreign practice of ensuring the fulfilment of contractual obligations was analysed, and the possible directions of its implementation in the domestic legal space were determined. Gaps in legislative regulation and problems of practical implementation in ways to ensure the implementation of agreements were identified. The author proposed the definition of ways to ensure the implementation of contracts. The findings are valuable for legislative initiatives and for the practical activities of the parties to contractual obligations in terms of choosing the most effective way to secure the contracts they enter into.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.060 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.034 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".