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Record W4220921153 · doi:10.1002/iir.1457

Evolution of consumer bankruptcy in Poland: A chance for a new life for insolvent debtors?

2022· article· en· W4220921153 on OpenAlexvenueno aff
Monika Maśnicka, Joanna Kruczalak‐Jankowska

Bibliographic record

VenueInternational Insolvency Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Contract Law
Canadian institutionsnot available
Fundersnot available
KeywordsBankruptcyInsolvencyLegislatorLegislationBusinessConsumer Protection ActDebtorLaw and economicsDebtFresh StartEconomicsLawFinanceCreditorPolitical science

Abstract

fetched live from OpenAlex

Abstract This article discusses the issue of the evolution of consumer bankruptcy in Poland which was introduced into Polish law in 2009. The authors explain why the legislator abstained from introducing consumer bankruptcy along with a huge reform of insolvency framework in 2003. They present different approaches of the legislator towards consumer bankruptcy – from a very restrictive one which excluded most consumers from bankruptcy proceedings to a liberal one that allows dishonest debtors to benefit from debt relief. Moreover, the influence of legislation regarding consumer bankruptcy on the effectiveness of insolvency courts is discussed. Each of the approaches caused certain problems in practice. Liberalization of the rules on consumer bankruptcy led to an increasing number of consumer bankruptcy cases which could be barely processed by insolvency courts to the detriment of commercial bankruptcies and restructurings. The authors present the latest change of the law regarding consumer insolvency which – due to its novelty – has not received enough attention yet. They also provide a preliminary assessment of the new rules, which they consider imperfect.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.058
GPT teacher head0.371
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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