The Strategies of the International Chamber of Commerce to Eliminate Double Taxation
Bibliographic record
Abstract
ABSTRACT This article focuses on the role of the International Chamber of Commerce (ICC) in developing the regime on the elimination of double taxation in the twentieth century. The objective of the article is to determine the ICC’s strategies and its structural advantages in developing the regime and contextualize these strategies in a broader socio-legal and historical context. The article adopts the interactional theory of Jutta Brunée and Stephan Toope to emphasize the actor-oriented outlook upon the development of the regime on double taxation. It relies on the micro-and macro-histories teased out from archival sources, biographies of prominent decision-makers, and deliberations of committee members in the League of Nations and the United Nations. The article concludes that the ICC is a strategic player within the community of practice in the international tax regime, which utilized its structural advantages and employed different strategies to facilitate the elimination of double taxation.
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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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.018 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".