Problems of distinguishing legal entities of public and private law
Bibliographic record
Abstract
The article is devoted to the issue of the distinction between legal entities of public and private law, which remains debatable in Ukraine, given the insufficiency of legally established criteria for their distinction. The analysis of the legislation of the USA, Canada, European and post-Soviet countries, the practice of the ECHR regarding the definition of the scope and legal status of legal entities of public law. It is revealed that the emergence and content of the status of legal entities of public law in specific foreign legal systems has practically no standard approaches, and largely depends on various national-state and cultural-historical features of their development, and the status of a legal entity of public law is usually acquired by sufficiently arbitrarily granting it to them by the state. It is proved that in the absence of a special law and a legal definition of the list of legal entities of public law, a situation of certain legal uncertainty is created, which is a deficiency of the legislation. The criteria proposed by lawyers for distinguishing legal entities of public law from legal entities of private law are considered. It is argued that a new impetus for the discussion on the distinction between legal entities of public and private law is caused by the provisions of anti-corruption legislation on the declaration of income of politically exposed persons, and amendments are proposed to subparagraph «a» of paragraph 2 of part one of Article 3 of the Law of Ukraine «On Prevention of Corruption». Key words: legal entity, legal entity of public law, legal entity of private law, state enterprises, municipal enterprises
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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 | 0.022 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.009 | 0.031 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.008 |
| 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".