The Unruly World of Tax: A Proposal for an International Tax Cooperation Forum
Bibliographic record
Abstract
International cooperation in tax policy is deeply fractured. Inconsistencies, loopholes, and ineffective mechanisms—which could be avoided if real collaboration among countries existed—have created significant inefficiency losses for decades. This Article focuses on the institutional infrastructure underlying international cooperation in tax issues and argues that the current forums in which such cooperation is encouraged do not provide an adequate platform in which countries with similar interests can effectively make a collaborative effort. To facilitate cooperation, this Article proposes to create a new institution currently missing from the international tax policy-setting arena: an informal forum for coordination among countries that share similar interests in tax policy, inspired by the model of “Like Minded Groups” in international organizations. This forum will enable countries that share similar interests to cooperate and reach understandings about necessary policy adaptations. We identify two major projects that this forum could promote—efforts to curtail tax evasion and efforts to harmonize various aspects of tax policy. We argue that this model might have significant advantages in promoting cooperation, reducing the “competitiveness” threat, advocating coordinated policies, and overcoming external and domestic pressures. In light of the current challenges in the field of tax policy, and the difficulties in forming international cooperation within the current institutional framework, the proposed model is worth serious discussion and consideration.
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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 | 0.026 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.018 | 0.018 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.046 | 0.018 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".