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Record W2611272792

The Fictitious Payee After Teva v. BMO: Has the Pendulum Swung Back Far Enough?

2016· article· en· W2611272792 on OpenAlexaffabout
Benjamin Geva

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Systems and Judicial Processes
Canadian institutionsYork University
Fundersnot available
KeywordsChequeAccounts payableBusinessPaymentNegotiable instrumentAccountingFinanceComputer scienceComputer security
DOInot available

Abstract

fetched live from OpenAlex

Under Section 20(5) of the Bills of Exchange Act (‘‘BEA s. 20(5)”) where on a bill of exchange ‘‘the payee is a fictitious or non-existing person, the bill may be treated as payable to bearer.” A bill of exchange includes a cheque. Where BEA s. 20(5) applies to a cheque, its effect is to reallocate forged endorsement losses from banks involved in the collection and payment of the cheque to the drawer. Quite recently, in commenting on Raza Kayani LLP v. Toronto-Dominion Bank, I highlighted the ongoing confusion in the judicial interpretation of BEA s. 20(5) (‘‘Kayani Comment”). That comment does not appear to have been available to the judges of the Ontario Court of Appeal in subsequently rendering their judgement in Teva Canada Ltd. v. Bank of Montreal (‘‘Teva”). At the same time, in invoking a policy rationale, in addition to relying on a precedent, the Court in Teva acknowledged my position as had been already expressed in a previous writing on the subject. It thus recognized that as regards to cheque fraud committed by an insider in and on a corporate drawer BEA s. 20(5) is to be interpreted as allocating losses to ‘‘the drawer, who typically is better positioned to discover the fraud or insure against it.” Accordingly, the Court in Teva distinguished Boma Manufacturing Ltd. v. Canadian Imperial Bank of Commerce (‘‘Boma”) and thus restored a measure of consistency between law and good policies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.906
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.022
GPT teacher head0.264
Teacher spread0.242 · 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; both teacher heads agree on what is shown here.

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 routes2
Has abstractyes

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