Notice bibliographique
Résumé
6.For each jurisdiction, the review covers the domestic legal and administrative framework, the exchange of information framework and measures in place to ensure the confidentiality and appropriate use of CbC reports. Key findings 7.The key findings of the fifth annual peer review are as follows: Domestic legal and administrative framework: Over 100 jurisdictions have a domestic legal framework for CbC reporting in place.In addition, a number of jurisdictions have final legislation approved that is awaiting official publication.In this peer review report, 28 jurisdictions have received a general recommendation to put in place or finalise their domestic legal or administrative framework and 27 jurisdictions received one or more recommendations for improvements to specific areas of their framework.Furthermore, two jurisdictions finalised legislation during this peer review period but it has not been possible to carry out a review of that legislation.A review of the legislation will take place in the next peer review. Exchange of information framework: Of the jurisdictions included in this review, 82 jurisdictions have multilateral or bilateral competent authority agreements in place. Confidentiality: Of the jurisdictions included in this review, 88 have undergone an assessment by the Global Forum on Transparency and Exchange of Information for Tax Purposes (the Global Forum) concerning confidentiality and data safeguards in the context of implementing the AEOI standard, and did not receive any action plan. Appropriate use: Of the jurisdictions included in this review, 64 jurisdictions have provided detailed information, enabling the Inclusive Framework to obtain sufficient assurance that measures are in place to ensure the appropriate use of CbC reports. 8.During the course of this peer review, a number of jurisdictions reported delays in the implementation of CbC reporting, or in the filing and exchange of CbC reports, resulting from the impact of the COVID-19 pandemic.As these concern issues beyond the control of tax administrations, and there is no reason to believe they will persist once the pandemic comes to an end, these delays are not highlighted in each jurisdiction's peer review and no recommendation is made.If delays continue into periods covered by future peer reviews, they will be considered in the context of the global situation at that time. 9.A number of Inclusive Framework members are not included in this peer review report, either because they joined the Inclusive Framework after 1 October 2021 (at which point it was too late to incorporate them into the current peer review process) or they opted out of the peer review in accordance with the peer review terms of reference.Jurisdictions opting out of the peer review are required to confirm that they do not have any resident entities that are the UPE of an MNE Group above the consolidated group revenue threshold and that they will not require local filing of CbC reports.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,008 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,614 | 0,369 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».