Financiarisation, gouvernance et enjeux éthiques dans les restructurations industrielles
Bibliographic record
Abstract
Dans le cadre de la restructuration d’entreprise du holding Papiers White Birch, les retraités ont vu leur fonds de retraite fondre alors que l’entreprise a demandé la fermeture du régime de retraite à prestations déterminées. Comment notre système juridique arrive-t-il à permettre un tel dénouement qui semble en faveur des acteurs économiques au détriment des retraités ? À partir de l’étude de cas de Papiers White Birch, cette recherche ouvre la boîte noire du déroulement de la restructuration, analyse les enjeux éthiques et interroge la nature des notions d’intérêt public et de justice sociale au cœur du processus canadien de restructuration d’entreprise sous la Loi sur les arrangements avec les créanciers des compagnies (LACC). Cette étude permet de revisiter la notion de justice sociale à partir du concept de capabilité développé par Amartya Sen et d'en proposer une application en contexte de restructuration sous la LACC.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".