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경쟁법상 부당한 공동행위의 형사처벌에 따르는 법리적 쟁점

2019· article· ko· W3044181491 sur OpenAlexaboutno aff
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Notice bibliographique

Revue경쟁법연구 · 2019
Typearticle
Langueko
DomaineEconomics, Econometrics and Finance
ThématiqueMerger and Competition Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSanctionsCartelPolitical scienceAntipathyEnforcementCompetition (biology)CriticismInternational communityCompetition lawLawLaw and economicsBusinessInternational tradeEconomicsIncentivePoliticsMonopoly
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Criminal punishment for cartels began with Article 1 of the U.S. Sherman Act, which has set a strong antipathy against cartels and monopolies at the time of the enactment of the Act. Against this backdrop, the so-called ‘conspiracy-centered approach’ was adopted. Specifically this approach could be explained as as ‘agreement’-oriented components that do not take into account their implementation or the consequences of implementation, a prohibition that is not exceptionally permissible, and strong criminal sanctions that include jail terms for individuals involved. On the other hand, the circumstances behind creating competition laws for the EU community and its members are clearly distinct from those of the United States. That is, in the background of the lack of experience in moral criticism of cartels, the EU Community and Member States Competition Law has adopted an administrative-regulatory approach, which has centered around specialized regulators, to determine whether an agreement is prohibited by combining “effects or consequences” with the agreement itself. Fines, administrative sanctions, have played a major role in enforcement. However, the introduction or reinforcement of criminal sanctions to enhance the effectiveness of cartels’ regulations is being noticeable due to the strengthening of awareness of problems with international cartels in the 1990s and the global spread of the leniency program that began successfully operating in the U.S. Currently, 12 countries among EU member states enforce criminal sanctions against cartels, while others, Canada, Australia, Brazil, Israel, Mexico and South Korea, do so. Many of these countries have adopted or strengthened them through legal revisions since the 2000s, showing a distinct tendency toward so-called “criminalization.” And in Korea, this trend is felt in the discussion surrounding the abolition of the “exclusive accusation system”. In the case of Korea, the exclusive accusation system could be said to have been an institutional mechanism that allowed criminal sanctions to exist in a coherent manner within the framework of administrative regulation, and thus mitigated legal and procedural problems that followed criminal sanctions to some extent. In other words, an independent regulator with expertise in the Fair Trade Act has been, to some extent, restraining the problems arising from the presence of both administrative and criminal enforcement by leaving the right to decide whether or not to initiate criminal enforcement. In particular, criminal punishment of the individual involved had been supported in the light of strengthening the deterrent effect without due consideration of its legal implications, and it is thought that critical review of it from the criminal law, particularly the question of ambiguity of the subject and the substance of legality, could never be omitted. It can be expected that the recently discussed abolition of the exclusive accusation system will bring about significant changes to the existing cartel’s enforcement system, that, among other things, the criminal procedure of administrative procedures cannot rule out the possibility of fundamentally changing the relationship between regulators and undertakings under competitive law, and that the benefits of enhancing the deterrent effect may not be significant due to the increase in regulatory costs associated with criminal procedures.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,836
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0880,086

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,017
Tête enseignante GPT0,199
Écart entre enseignants0,182 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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