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Record W2590183587 · doi:10.1017/cbo9781107337671

Value Added Tax

2015· book· en· W2590183587 on OpenAlexaff
Alan Schenk, Victor Thuronyi, Wei Cui

Bibliographic record

VenueCambridge University Press eBooks · 2015
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsValue-added taxPrincipal (computer security)Presentation (obstetrics)Tax evasionValue (mathematics)Tax reformGovernment (linguistics)Indirect taxDouble taxationTax policyChinaResource (disambiguation)Public economicsTax avoidanceDirect taxEconomicsPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

This book integrates legal, economic, and administrative materials about the value added tax (VAT) to present the only comparative approach to the study of VAT law. The comparative presentation of this volume offers an analysis of policy issues relating to tax structure and tax base as well as insights into how cases arising out of VAT disputes have been resolved. Its principal purpose is to provide comprehensive teaching tools - laws, cases, analytical exercises, and questions drawn from the experience of countries and organizations around the world. This second edition includes new VAT-related developments in Europe, Asia, Africa, and Australia and adds new chapters on VAT avoidance and evasion and on China's VAT. Designed to illustrate, analyze, and explain the principal theoretical and operating features of value added taxes, including their adoption and implementation, this book will be an invaluable resource for tax practitioners and government officials.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.073
Threshold uncertainty score0.243

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0730.036

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 head0.052
GPT teacher head0.200
Teacher spread0.148 · 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

Citations32
Published2015
Admission routes1
Has abstractyes

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