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Record W2274132867 · doi:10.3917/fina.362.0037

Too much of a good thing? The impact of a new bankruptcy law in Canada

2016· article· fr· W2274132867 on OpenAlexaboutno aff
Timothy S. Fisher, Jocelyn Martel

Bibliographic record

VenueFinance · 2016
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

L’adoption par le Canada d’une nouvelle loi sur la faillite plus favorable aux débiteurs a multiplié par dix la proportion des entreprises insolvables optant pour la réorganisation par rapport à la liquidation. Sur la base d’un échantillon aléatoire d’entreprises ayant soumis un plan de réorganisation avant et après la nouvelle loi, nous concluons que, comparativement aux entreprises en réorganisation avant la loi de réforme sur la faillite, les entreprises en réorganisation sous la nouvelle loi sont de plus petite taille, affichent une santé financière plus fragile et déclarent des créances gouvernementales significativement plus élevées. En accordant un pouvoir de négociation accru aux débiteurs, la nouvelle loi sur la faillite a eu deux effects importants sur les créanciers : une réduction de 25 % du taux de remboursement des créances non-garanties et un allongement de la période de réorganisation. L’analyse montre également que la réforme de la loi a eu deux effets non-anticipés. Elle a accru le rôle indirect de l’état dans le financement des petites entreprises insolvables et donné une plus grande incitation aux créanciers garantis à préférer d’autres alternatives à la réorganisation financière en cas d’insolvabilité.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.209
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2016
Admission routes1
Has abstractyes

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