“Come and talk”: The insolvency judge as <scp>de‐escalator</scp>
Bibliographic record
Abstract
Abstract How insolvency courts handle conflicts is an important aspect of the Directive on preventive restructuring frameworks and it has become more important in the current COVID‐19 crisis, as a result of which insolvencies are or will be on the rise. Insolvency courts are one of the key actors that can impact the length and costs of conflicts, and, consequently, the effectiveness and efficiency of insolvency proceedings. However, there is a lack of empirical research that examines when, why and how insolvency courts prevent actual or potential conflicts. This article reports the results of an empirical study that explored the strategies used by insolvency judges in the Netherlands to resolve conflicts and to prevent a dispute from becoming one. The results show that insolvency courts deploy “under the radar” mediation‐like strategies to prevent actual and potential conflicts involving insolvency practitioners, enhancing the speed and cost‐effectiveness of the winding‐up of cases in the perceptions of stakeholders. Consequently, insolvency judges do not only act as adjudicators in court proceedings, but also take on mediation‐like roles, at least in some jurisdictions. Limitations and challenges of these roles are discussed. The findings of this study are relevant for determining and regulating the roles and tasks of insolvency judges.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".