Bibliographic record
Abstract
States are on the verge of a new form of global competition. Some have taken unilateral measures to tax multinational profits that they would typically not be able to tax, at least not according to conventional international tax concepts and rules. Others have threatened to retaliate with economic countermeasures to protect their tax base and corporate residents. The recent attempt of the OECD to build consensus for a global tax compact has so far proven unsuccessful due to broad disagreement about how taxing rights should be equitably distributed between countries. As policymakers and tax scholars increasingly call into question long-standing theories of international taxation, the concept of inter-nation equity plays a pivotal role as a guiding principle in determining how to divide the international tax base among states. Inter-nation equity is one of the most ubiquitous concepts appearing in international tax policy discussions and yet one of the most understudied in tax scholarship. This Article introduces a comprehensive normative analysis of inter-nation equity by discussing how the concept should reconcile the two primary goals of international allocation of taxing rights: on the one hand, the concern of states to preserve their tax sovereignty and, on the other hand, the need to promote some degree of redistribution to address the challenges of global poverty and inequality. This Article further explains how a similar notion of inter-nation equity has developed in other areas of international law and discusses some practical implications for tax policy design.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".