Septembre 1994Commercial Bankruptcy and Financial Reorganization in Canada *
Bibliographic record
Abstract
Jocelyn Martel détient un doctorat en économie de l’Université de Montréal. Il poursuit présentement des études post-doctorales au CIRANO. Le professeur Martel se spécialise en analyse économique des faillites et de la réorganisation financière, ainsi qu’en micro-économie appliquée. Il s’intéresse particulièrement au comportement stratégique des entreprises et créanciers en difficultés financières. Une grande partie de son travail consiste à élaborer de nouveaux modèles de comportement de la firme dans un contexte d’insolvabilité, à construire des séries de données originales sur les entreprises en faillite et en réorganisation, à tester les théories existantes dans ce domaine, ainsi qu’à évaluer le fonctionnement du système de faillite canadien. Une autre partie de ses recherches consiste en un travail empirique sur l’impact de l’investissement en capital humain spécifique sur la structure de capital des entreprises. Jocelyn Martel has a Ph.D. degree in economics from the University of Montreal. He is currently pursuing post-doctoral studies at CIRANO. Dr. Martel specializes in the economic analysis of bankruptcy and financial reorganization and in applied microeconomics. He is particularly interested in examining the strategic behaviour of firms and creditors in the context of financial distress. The main body of his work deals with developing new models of firm behaviour in insolvency, building original data sets on bankrupt reorganized firms, to test existing and new theories in the area as well as to evaluate the functioning of the bankruptcy system in Canada. He is also doing empirical work on the impact of specific human capital investment on the capital structure of the firm.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.002 |
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".