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Record W7066350207

The History of Canada’s Double Tax Conventions

2021· article· en· W7066350207 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle Detector Development and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsTax treatyInternational taxationDouble taxationLeagueTax lawTax reformDirect taxBridging (networking)
DOInot available

Abstract

fetched live from OpenAlex

This book analyses the evolution of tax treaties practices from the early days of the history of international taxation until the beginning of the BEPS era.\nWhy this book?\nThe design of international tax law cannot be described without recourse to its extensive history. By looking at the evolution of tax treaties, valuable insight is gained as regards the causes behind the most recent shift towards renewed international tax coordination in the framework of the BEPS Project. This book analyses how tax treaties have evolved, from the early days of the history of international taxation until the beginning of the BEPS era, by collecting the outcome of joint research on the development of international tax law. It consists of a wide range of papers bridging the existing gap between the history of international law, economic history and the history of international cooperation.\nIn this context, it also spells out the importance of the role of early institutions such as the International Chamber of Commerce and the League of Nations, as well as the International Fiscal Association and the OEEC/OECD, and helps to highlight their fundamental influence. The book is the result of the conference “History of Double Taxation Conventions”, which took place from 3-5 July 2008 in Rust/Neusiedler See. It consists of 30 contributions exploring the development of the tax treaty practices of 30 countries and, additionally, three cross-sectional contributions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.150
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0170.007
Scholarly communication0.0080.003
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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