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Record W2938146308

Payment Transactions under the E.U. Second Payment Services Directive – An Outsider’s View

2019· article· en· W2938146308 on OpenAlexaff
Benjamin Geva

Bibliographic record

VenueeYLS (Yale Law School) · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Governance and Law
Canadian institutionsYork University
Fundersnot available
KeywordsPayment service providerPaymentDirectiveCompetition (biology)BusinessPayment orderCommissionRationalisationPayment systemCommerceLawFinanceEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

In its proposal for a Directive on payment services in the internal market (hereafter: the Proposal), the Commission of the European Communities (“the Commission”) purported to provide for “a harmonised legal framework” designed to create “a Single Payment Market where improved economies of scale and competition would help to reduce cost of the payment system.” Being “complemented by industry’s initiative for a Single Euro Payment Area (SEPA) aimed at integrating national payment infrastructures and payment products for the euro-zone,” the Proposal was designed to “establish a common framework for the Community payments market creating the conditions for integration and rationalisation of national payment systems.” Focusing on electronic payments, and designed to “leave maximum room for self-regulation of industry,” the Proposal purported to “only harmonise what is necessary to overcome legal barriers to a Single Market, avoiding regulating issues which would go beyond this matter.” Stated otherwise, the measure was designed to fall short of providing for a comprehensive payment law.

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)0.013
metaresearch head score (Gemma)0.023
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: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0080.009
Scholarly communication0.0200.009
Open science0.0030.005
Research integrity0.0440.020
Insufficient payload (model declined to judge)0.0080.004

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 head0.224
Teacher spread0.209 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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