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Record W2291618755 · doi:10.14288/1.0077438

Reflections on the Canadian payments systems: from manual clearing to electronic funds transfers

2009· article· en· W2291618755 on OpenAlexaboutno aff
Alison L Kirby

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBanking Systems and Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsClearingBusinessPaymentElectronic funds transferFinanceActuarial science

Abstract

fetched live from OpenAlex

The Canadian payments system encompasses not only those traditional systems which facilitate the processing of paper payment instructions through the Automated Clearing and Settlement System (ACSS) and or the Bank of Canada but those electronic funds transfer (EFT) systems which are capable of processing payment instructions in purely electronic form. Access to the payments system is a key element in the retail and financial services sectors' bid to remain competitive on both national and global scales. Moreover, a complete system of electronic payments will eventually reduce the need for credit cards and, to the extent that it increases the use of deposits for payment purposes, it will reduce the need for currency and cheques as well. In other words, a truly national electronic funds transfer system will act not only as a "payments system" or financial communications system that will carry payment instructions but a "payment mechanism" which will replace payment for goods and services by cash or cheques. This paper provides an overview of the national payments systems and identifies some of the problems which have arisen as a result of the changes to the largely paper based systems brought about by the electronic banking age. It identifies the technological advances made in the payments area, the traditional right or obligation arising as a result of the bank-customer relationship, if any, which has been effected by the technological advance, it briefly examines how the technological advance impacts on this right or obligation; and it raises questions about whether the traditional right or obligation needs to be protected, modified or eliminated and, if so, in what matter. In the end, it is hoped that this paper will serve as a wake up call to consumers and academics about the importance of and the need for greater access to information about the national payments system.

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)0.007
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.212
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.006
Science and technology studies0.0220.019
Scholarly communication0.0170.007
Open science0.0030.004
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0140.001

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.

Opus teacher head0.018
GPT teacher head0.202
Teacher spread0.184 · 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
GenreOther

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
Published2009
Admission routes1
Has abstractyes

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