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Record W2289402067

Des réponses efficaces aux planifications fiscales agressives : Leçons à retenir des autres juridictions : Fascicule 4 : Royaume-Uni - Règles de divulgation = Effective Responses to Aggressive Tax Planning : What Canada Can Learn from Other Jurisdictions : Instalment 4 : United Kingdom - Disclosure Rules

2009· article· fr· W2289402067 on OpenAlexaboutno aff
Gilles R Larin, Robert Duong, Lyne Latulippe

Bibliographic record

VenueKnowledge UdeS (Institutional Deposit of the University of Sherbrooke) · 2009
Typearticle
Languagefr
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Résumé: Ce présent fascicule porte sur les règles de divulgation du Royaume-Uni. L'outil présente des similitudes avec les règles de divulgation au Canada portant sur les abris fiscaux. Ce fascicule situe d'abord le contexte dans lequel s'inscrivent les règles de divulgation. Il identifie les principales modalités d'application des règles ainsi que les enjeux de leur application pour chacun des groupes d'intervenants. Nous formulerons ensuite des conclusions quant à l'application de cet outil. À notre avis, le dépistage des planifications audacieuses selon leur degré de conformité aux normes commerciales permet de circonscrire de manière prévisible et flexible les planifications qui posent un risque d'évitement. Les divers groupes d'intervenants pourraient cependant diverger d'opinions quant aux normes commerciales qu'il serait opportun d'appliquer dans une situation donnée. Les seuils de pénalité en cas d'inobservation des règles ne doivent pas être excessifs si l'on veut favoriser la production de renseignements et permettre à l'administration fiscale d'adopter rapidement des règles spécifiques pour annuler les avantages fiscaux découlant d'opérations d'évitement. Cependant, l'absence de paramètres dans la loi fiscale définissant la notion d'évitement implique que tous les groupes d'intervenants, y compris les tribunaux, divergeront d'opinion sur les caractéristiques de ces opérations. Les contribuables et les conseillers fiscaux font alors face à la possibilité de produire des déclarations de renseignements à l'égard d'opérations qui sont conformes aux objets de la loi fiscale. La multiplication des règles spécifiques antiévitement et, dans certains cas, la possibilité qu'elles entrent en vigueur de façon rétroactive a relancé le débat au Royaume-Uni sur l'utilité d'une règle générale antiévitement. Par souci d'équité et prévisibilité dans l'application de la loi, l'administration fiscale doit minimiser le fardeau additionnel d'observation imposé par les règles de divulgation sur les contribuables et les conseillers de manière à les appliquer de façon cohérente en fonction des objets de la loi. Nous croyons que l'efficacité des règles de divulgation dépend étroitement du poids du privilège du secret professionnel de l'avocat en matière fiscale. À notre avis, les contribuables pourraient devoir produire des renseignements relativement aux faits et à la structure de l'opération dont ils ont connaissance et qui sous-tendent les avantages fiscaux qu'ils réclament. Une telle obligation s'inscrit dans le cadre d'un régime d'autocotisation. Les tribunaux devront dissiper les incertitudes quant à l'obligation des conseillers de produire les opinions juridiques rendues à leurs clients, plus particulièrement eu égard aux objets de nature fiscale poursuivis par ces derniers dans une opération.||Abstract: This instalment deals with the United Kingdom’s disclosure rules, which have similarities with Canada’s disclosure rules on tax shelters. We begin by describing the context of the disclosure rules. We then identify their general application details as well as the issues of the application for each group of stakeholders. Next, we formulate conclusions on the application of these disclosure rules. In our view, detection of aggressive planning schemes according to the extent to which they comply with business standards helps to predictably and flexibly define schemes that carry a risk of avoidance. Various groups of stakeholders may hold different views as to the business standards that could usefully be applied in a given situation. The penalty thresholds in case of breach of the rules must not be excessive if the tax administration wishes to encourage filing of information and quickly adopt specific rules to withdraw tax benefits arising from tax avoidance schemes. However, the lack of parameters in the tax law defining the concept of avoidance implies that all groups of stakeholders, including the courts, will hold differing opinions on the characteristics of these arrangements. Taxpayers and tax advisers then face the possibility of filing information returns regarding arrangements that comply with the objects of the tax law. The proliferation of specific anti-avoidance rules and, in certain cases, the possibility that they apply with retroactive effect have revived the debate in the United Kingdom on the usefulness of a general antiavoidance rule. In the interests of fairness and predictability in the application of the law, the tax administration must minimize the additional compliance burden imposed by disclosure rules on taxpayers and tax advisers in order to apply them consistently according to the objects of the law. We believe that the effectiveness of disclosure rules is tied closely to the importance of legal professional privilege in tax matters. In our view, taxpayers may be required to file information on the facts and structure of the arrangement they are aware of and that underlie the tax benefits they claim. Such an obligation is part of a self-assessment system. The courts will have to dispel the uncertainty regarding the obligation of advisers to produce the legal opinions supplied to their clients, more particularly in view of clients’ tax purposes in an arrangement.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.232
Teacher spread0.214 · 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
Published2009
Admission routes1
Has abstractyes

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