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Record W4395027663 · doi:10.59403/1rk780x019

Chapter 19: Switzerland

2018· book-chapter· en· W4395027663 on OpenAlexaboutno aff
P. Hongler, L. Schlegel

Bibliographic record

VenueEC and international tax law series. · 2018
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicTaxation and Legal Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

Why this book? Taxation of Intellectual Property under Domestic Law, EU Law and Tax Treaties, comprising the proceedings and working documents of an annual seminar held in Milan in November 2017, is a detailed and comprehensive study on the taxation of intellectual property (IP). It begins with a comparative analysis of the domestic private law aspects of IP and the domestic tax regimes applicable to profits deriving from the utilization of IP. It next examines the taxation of IP under EU law, with a particular emphasis on (i) the EU fundamental freedoms and State aid, and (ii) the open issues in the implementation of the EU Interest and Royalty Directive. The book then moves to selected tax treaty issues. In particular, it analyses (i) the historical background and the policy of article 12 of the OECD Model Convention; (ii) the meaning of “royalties” and overlapping between articles 7, 12 and 13 of the OECD Model Convention; (iii) royalties in the context of the OECD Multilateral Instrument under the limitation on benefits (LOB) provision and the principal purpose test (PPT) clause; and (iv) certain selected issues on cross-border transfers of IP. Individual country surveys provide an in-depth analysis of the domestic tax regimes and actual tax treaty application and practices by various states, including Australia, Austria, Brazil, Canada, China (People’s Rep.), France, Germany, Italy, the Netherlands, Spain, Switzerland, the United Kingdom and the United States. This book presents a unique and detailed insight into the taxation of intellectual property in an international context and is therefore an essential reference source for international tax students, practitioners and academics. Downloads Sample excerpt, including table of contents This book is part of the EC and International Tax Law Series View other titles in the series Editor(s) Guglielmo Maisto Contributor(s) Paolo Arginelli, Celeste M. Black, Alberto Brazzalotto, Patricia A. Brown, Sophie Chatel, Robin Damberger, Robert J. Danon, Mathieu Daudé, David N. de Ruig, Sjoerd Douma, Anne Fairpo, Elizabeth Gil García, Hans-Peter Gradwohl, Peter Hongler, Michael D. Knobler, Na Li, Sean P. McElroy, Adolfo Martín Jiménez, Leonardo F. de Moraes e Castro, Larissa B. Neumann, Jacques Sasseville, Joel Scheuerman, Livia Schlegel, Florian Schmid, Julia Ushakova-Stein, Matthias Valta, Zoya Zalmai

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.890
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0260.002

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 head0.023
GPT teacher head0.229
Teacher spread0.207 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

Explore more

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