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Record W3013444420

El cártel del dinero: Algunas cuestiones suscitadas a propósito diones de la Comisión europea de 16 de mayo de 2019 en relación con práctie dos Deciscas anticompetitivas en el mercado de divisas

2019· article· es· W3013444420 on OpenAlexaboutno aff
Laura González Pachón

Bibliographic record

VenueRevista de derecho de la competencia y la distribución · 2019
Typearticle
Languagees
FieldEnvironmental Science
TopicFinance, Taxation, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEurosEuropean unionPolitical scienceTreatyHumanitiesEuropean commissionLineaWelfare economicsInternational tradeBusinessEconomicsArtLaw
DOInot available

Abstract

fetched live from OpenAlex

espanolLa Comision europea con fecha de 16 de mayo de 2019 ha impuesto multas por un importe total de 1,07 millones de euros a cinco entidades financieras que operan en la Union Europea, al considerar probada su participacion en la comision de practicas anticompetitivas en el mercado de cambio de divisas. La trascendencia de estas decisiones, se debe no solo al volumen de las multas impuestas, sino tambien al numero de divisas afectadas, cinco de las cuales operan en el Area Economica Europea: la libra esterlina, el franco suizo, la corona danesa, sueca y noruega, el yen japones, asi como el dolar americano, canadiense, neozelandes y australiano. Se trata de una vulneracion del art. 101 TFUE y del art 53 del Acuerdo EEE que prohiben los carteles y otras practicas comerciales restrictivas. EnglishOn May 16th 2019, The European Commission has fined with a total amount of 1.07 billion five financial entities operating in the EU for taking part in anti-competitive behaviour or practices in the Currency Exchange Market. The significance of these decisions is not only due to the volume of the fines set, but to the number of foreign exchange affected, five of which are used in the European Economic Area: the British Pound, Swiss Franc, Danish, Swedish and Norwegian crowns, Japanese Yen, as well as US, Canadian, New Zealand and Australian Dollars. It is a violation of article 101 of the Treaty on the Functioning of the European Union (TFEU) and article 53 of the EEA Agreement, that prohibit cartels and other restrictive business practices.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
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 head0.003
GPT teacher head0.248
Teacher spread0.244 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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