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Record W138681698

International Tax Competition: The Last Battleground of Globalization

2011· article· en· W138681698 on OpenAlexaff
Arthur J. Cockfield

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsQueen's University
Fundersnot available
KeywordsTax competitionTax policyInternational tradeGlobalizationTax avoidanceGovernment (linguistics)BattleDouble taxationInternational economicsTax havenEconomicsCompetition (biology)Investment (military)Foreign direct investmentInternational taxationTax reformBusinessMarket economyPolitical sciencePublic economicsPoliticsLaw
DOInot available

Abstract

fetched live from OpenAlex

Increasingly linked by regional and global ties, national economies depend more than ever on international investments and trade. While trade and investment have become international, however, taxation has remained national, preserving and strengthening one of the few remaining barriers to cross-border economic flows. Given their general unwillingness to be bound by multilateral tax agreements, governments increasingly study the tax policies in place elsewhere to ensure that their tax rules governing the treatment of cross-border investments are ‘competitive’ with those of foreign tax regimes. To highlight the relevant policy issues, the article discusses the challenges of taxing one cross-border investment, namely the Hollywood blockbuster movie 300, which was loosely based on Herodotus’ account of the Battle of Thermopylae in The Histories. A final section touches on the ways that international tax policy analysis struggles to identify optimal laws and policies given the reality of a non-cooperative government setting.

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)0.003
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.011
Scholarly communication0.0100.009
Open science0.0010.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0070.001

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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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
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

Citations2
Published2011
Admission routes1
Has abstractyes

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