Flying With the EU : The Movement Towards a Global Aviation Hegemony
Bibliographic record
Abstract
This paper examines the European Unionʼs (EU) strategic use of Comprehensive Air Transport Agreements (CATAs) as instruments of norm diffusion and regulatory influence in international aviation.Focusing on four agreements with the United States, Canada, Qatar, and ASEAN.The research explores the aeropolitical dynamics that underpin these partnerships and assesses the effectiveness of the EUʼs efforts to export its regulatory norms.Proposing a theoretical framework that utilizes the contradiction of aeropolitical dynamics to examine the rationale of the parties in the agreement, the research attempts to identify tensions between regulatory convergence and sovereignty sentiments, as well as market liberalization and strategic national interest.Through a comparative analysis, the research hopes to reveal that while the EU has made significant efforts in shaping global aviation norms, its success is uneven and largely dependent on the partnerʼs regulatory capacity, geopolitical orientation, and willingness to internalize EU standards.Drawing on specific concepts from international relations theory such as strategic adaptation and norm localization, the research illustrates how international cooperation in aviation is characterized by complex, often contradictory dynamics.Utilizing the observations from the analysis, the research hopes to examine the effectiveness of the EUʼs attempt at norm diffusion.Ultimately, the research hopes to contribute to the understanding of how the EU leverages soft power, market access, and institutional arrangements to reshape international air transport governance.Table of Contents 1. Introduction 2. Premise of the Current Situation 3. The European Union as a Potential Aviation Power 4. The EU Comprehensive-style Air Transport Agreements 5. Contrasting the Dynamics of the Aeropolitics 6.The European Unionʼs Norm Diffusion 7. Conclusion
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".