The legal restructuring framework in Poland: Does it help indebted enterprises avoid bankruptcy?
Bibliographic record
Abstract
Abstract The purpose of the article is to present the latest research regarding the usefulness of restructuring proceedings in Poland, which enterprises threatened with insolvency or already insolvent may use to avoid bankruptcy. Changes in the legal system in Poland in 2015 were ground‐breaking, as not only the bankruptcy law was amended, but also the legal system was enriched with a new Restructuring Law (in force from 2016). The contribution of this article is threefold. First, the specifics of the four types of restructuring proceedings and the main actions to be carried out during the proceedings are discussed. Second, an analysis of the phenomenon of enterprise restructuring in Poland has been conducted on the basis of statistical data published by the Ministry of Justice. Third, the effects of 533 restructuring proceedings opened against capital companies in the period 2016–2018 have been assessed. The results achieved have allowed for the formulation of initial conclusions on the usefulness of the legal debt restructuring framework in Poland for business entities experiencing temporary financial difficulties.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".