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Record W4406227963 · doi:10.1093/jiel/jgae054

Global justice in the reshaping of international tax

2024· article· en· W4406227963 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of International Economic Law · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsTechnocracyDecentralizationNormativeEconomicsEconomic JusticePillarTax policyInternational taxationLaw and economicsTax reformPublic economicsPolitical sciencePolitical economyLawNeoclassical economicsMarket economyPolitics

Abstract

fetched live from OpenAlex

Abstract Global digitalization and economic decentralization have reshaped the landscape of international tax policy, prompting substantial reforms led by the OECD, most notably its ‘two-pillar solution’ aimed at addressing the taxation challenges of the digital economy. This article contends that these reforms fall short of incorporating principles of global justice. The analysis critiques both the technical and normative flaws of prevailing international tax policy design approaches, revealing how its intricate, technocratic framework conceals underlying distributional biases and neglects the developmental needs of less advantaged states. It calls for international tax reforms centred on fairness, advocating for explicit consideration of distributional outcomes to ensure a more just and balanced allocation of resources and responsibilities across nations.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.267
Teacher spread0.245 · 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