Do International Organizations have a Territory? Some General Reflections and the Special Case of the European Union
Bibliographic record
Abstract
The article explores the largely overlooked question of whether international organizations have a defined territory, noting that founding treaties of bodies such as the World Trade Organization (WTO), the International Monetary Fund (IMF), or the World Bank generally remain silent on this issue. Many agreements establishing free trade areas in Africa, Asia, or the Americas even omit territorial definitions, with notable exceptions like the US–Mexico–Canada Agreement . The European Union (EU), however, stands apart, as its treaties expressly define territorial scope (Articles 52 Treaty on European Union and Article 355 of the Treaty on the Functioning of the European Union ), a reflection of its colonial legacy and evolving institutional practice. The analysis develops in two stages: first, it explains how EU law has created a distinct legal notion of “EU territory” through treaty provisions, case law, and institutional collaboration between EU and national authorities; second, it considers how courts and institutions have consolidated this concept in practice, including in areas such as border management, competition law, and extraterritorial application of EU rules. The article concludes with a “layered” approach, where the EU’s legal territory overlays the physical territories of Member States while remaining subject to international law. This layered conception demonstrates how the EU, unlike most international organizations, has gradually developed its own recognizable territorial dimension.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.015 | 0.071 |
| Scholarly communication | 0.026 | 0.027 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".