The Power of Boilerplate: Bilateralism, Plurilateralism, and the International Tax System
Bibliographic record
Abstract
How do states exercise power in complex, decentralized governance regimes? This article sheds light on this question by analyzing one of the pillars of the post-war economic order: the international tax regime. The taxation of multinational enterprises is governed by a system composed of thousands of Bilateral Tax Treaties signed between pairs of national governments. We argue that despite the bilateral nature of these treaties, their legal content is largely controlled by a small group of economically powerful governments. By drafting and promoting “boilerplate” legal language, and by leveraging network effects, OECD countries were able to build a coherent, encompassing, quasi-multilateral regime to govern the taxation of multinationals in most of the world. We test and find support for our arguments about the role of network effects and the power of boilerplate using inferential network analysis and an automated text analysis of a corpus of 3200 treaty texts.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".