Signaling in Financial Reorganization: Theory and Evidence from Canada
Bibliographic record
Abstract
Cet article propose un modèle de comportement de la firme en réorganisation financière dans lequel la structure du contrat de réorganisation, et plus particulièrement la répartition entre les paiements comptants et différés, est utilisée afin de transmettre de l'information aux créanciers non-informés sur la viabilité de la firme. Les prédictions du modèle sont testées à l'aide d'une banque de données originale de 393 entreprises canadiennes en réorganisation financière. L'analyse empirique confirme que la probabilité de succès en réorganisation augmente avec la proportion des paiements à court terme (3 à 6 mois) aux créanciers non-garantis, après avoir contrôlé pour la contrainte de liquidité des entreprises. De plus, la probabilité d'acceptation d'une proposition par les créanciers non-garantis augmente avec la proportion des paiements comptants (1 mois) et la probabilité de succès de la proposition telle qu'anticipée par les créanciers.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".