Revisions of the UN Tax Treaty Model – An Introduction to (Global) Inclusion and Equity From the Perspective of Developing States
Bibliographic record
Abstract
This paper was specifically written for a Swedish tax journal and its audience. As a result, it assumes that the audience is less knowledgeable about the UN tax treaty model (UN MTC) and the general situation concerning the power relationship between the global north and south compared to, for instance, a Canadian audience. Nevertheless, it aims to provide initial insights in this power relationship and the role and function of the UN MTC. The UN MTC is often perceived as a reaction, or counterpart, to the OECD MTC as it attempts to level the playing field between developing and developed states when allocating taxing rights. The perspective of developing states is applied as a red thread throughout this paper in order to provide insight into the challenges that these states have been subject to, and the ones they are currently facing in connection to the developments surrounding the digital economy and the BEPS project. To summarize, the aim of this paper is to describe ongoing changes of the UN MTC, yet in order to truly understand soft law such as the MTC (its background, purpose and the future function of new revisions) one has to apply a holistic approach rather than applying a traditional legal method. As a result, the UN MTC is placed in a broader context, going beyond positive law. This results in the inclusion of supplementary sources besides the central UN material. Due to the prevalence of the OECD MTC and ongoing work at OECD level (primarily the BEPS project project) these sources need to be included as the UN does not act as a lone ranger, but instead is highly influenced by the developments at OECD and G20 level. The historical development of the UN MTC as a counterbalance to the forces of developed states in addition to the current (financial) situation in developing states are additionally fundamental in understanding the revisions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".