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National Report for Canada

2016· book-chapter· en· W4231348391 on OpenAlexaboutno aff
E Patrick Shea

Bibliographic record

VenueOxford University Press eBooks · 2016
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDebtorInsolvencyCreditorBankruptcyEntitlement (fair division)Statutory lawBusinessScope (computer science)Law and economicsLawActuarial sciencePolitical scienceEconomicsFinanceDebtComputer science

Abstract

fetched live from OpenAlex

Abstract This chapter discusses the law on creditor claims in Canada. The general approach is that all claims to which the debtor is subject when the reorganization or liquidation commences should be ‘brought into’ the proceeding, and creditors should receive a distribution based on their relative entitlement vis-à-vis the debtor. While the treatment of claims is generally consistent among the various insolvency proceedings, the proceedings are not identical, particularly regarding the priority of claims and procedures for establishing them. For example, the Bankruptcy and Insolvency Act provides a statutory claims procedure for both liquidations (bankruptcies) and reorganizations (proposals), but that procedure is not applicable in reorganization proceedings under the Companies’ Creditors Arrangement Act (CCAA) or in the distribution of the proceeds realized by a receiver. In reorganization proceedings under the CCAA, and where a receiver is appointed, the court determines the procedure to establish claims. The chapter then deals with insolvency claims, administration claims, and non-enforceable claims in turn. Each section covers: the definition and scope of the claim; rules for submission, verification, and satisfaction or admission of claims; ranking of claims; and voting and other participation rights in insolvency proceedings.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.277
Threshold uncertainty score0.925

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0060.001
Scholarly communication0.0060.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2770.082

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 head0.026
GPT teacher head0.184
Teacher spread0.159 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2016
Admission routes1
Has abstractyes

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