Irrelevant or Even Worse? The Vicious Dilemma of the New Tax Treaty Preamble
Bibliographic record
Abstract
The central thesis of this article is that the significance of the new preamble of the OECD model tax convention and the tax arrangements governed by the multilateral instrument should be evaluated with caution in the two areas where their proponents intend to see effects: (1) The preamble should not have effects on its own, since this could significantly undermine the integrity of the rule interpretation process. (2) The preamble should not serve as a complementary rule to the principal purpose test, since doing so would potentially amplify the already excessive impact of this general anti-avoidance rule and, in any case, further jeopardize its interpretation.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.019 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".