40 Years of consumer bankruptcy law in continental Europe: A qualitative analysis on the absence of consumer bankruptcy in the Western Balkan countries
Bibliographic record
Abstract
Abstract There are 12 countries in Europe without any consumer bankruptcy legislation, and almost half of them are located in the Western Balkans. The only available solution for debt repayment in the region is the enforcement procedure. This article identifies the reasons behind the non‐existence of consumer bankruptcy, and the challenges that Western Balkan countries face currently. Specifically, the article examines the rationale behind the need for consumer bankruptcy law enactment and the reasoning supporting the adoption of distinct consumer bankruptcy laws in the Western Balkans, encompassing economic, legal and cultural dimensions. Analysis of the absence of consumer bankruptcy legislation in the Western Balkans and the reasons behind it is terra incognita in the literature and the main contribution that the author offers. For this purpose, the author used qualitative research methods and conducted a qualitative study consisting of semi‐structured one‐on‐one interviews with legal professionals, policymakers and enforcement officials using open‐ended questions. The insights gained provide valuable implications for future consumer bankruptcy reforms in the region. The research contributes to the existing body of literature by offering a unique understanding of the phenomenon in European countries where currently there is no solution for debt adjustment.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".