Missed opportunities: The impact of EU institutional compartmentalization on EU climate diplomacy across the international regime complex on climate change
Bibliographic record
Abstract
The international governance of climate change no longer takes place in one single forum – the United Nations Framework Convention on Climate Change (UNFCCC) – but is increasingly spread across a multitude of fora that collectively make up the International Regime Complex on Climate Change (IRCCC). For ambitious actors with climate leadership ambitions, like the European Union (EU), the IRCCC offers the potential for connecting their activity across fora to achieve their climate objectives. Although the EU has appeared increasingly aware of the need to connect its activity across fora, the compartmentalization of EU institutional structures makes such connections unlikely. This paper seeks to understand the extent to which internal compartmentalization affects the EU’s ability to connect its activities across the IRCCC in support of its negotiation objectives across four climate agreements negotiated from 2015-2018: Paris Agreement (UNFCCC; 2015), CORSIA (ICAO, 2016), Kigali Amendment (Montreal Protocol; 2016), and the Initial Strategy on Reducing GHG Emissions (IMO, 2018). It answers the question: How do EU internal coordination structures affect the extent the EU demonstrates a comprehensive climate diplomacy across the IRCCC? Based on triangulation of official documents and 43 semi-structured interviews, it finds that internal EU compartmentalisation in general hinders the EU’s attempts to pursue a comprehensives climate diplomacy, though the compartmentalization worked in different ways across the four cases. Various combinations of a lack of communication channels, different priorities and policy framing, and a lack of resources and expertise contributed to situations where the EU was either limited in how it used specific fora or to the extent it used any fora at all to further its negotiation objectives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".