Connecting the dots? The European Union's diplomacy across the international regime complex on climate change
Bibliographic record
Abstract
The international governance of climate change is spread across a variety of overlapping fora dealing with specific aspects of the broader climate change challenge. These fora collectively make up the international regime complex on climate change. This dissertation examines the European Union’s (EU) diplomacy within this regime complex. Focusing on four multilateral negotiations within the international regime complex on climate change (UNFCCC Paris Agreement – 2015, ICAO CORSIA – 2016, Kigali Amendment to the Montreal Protocol – 2016, and the Initial IMO Strategy on Reduction of GHG Emissions from Ships – 2018), it identifies the specific ways the EU connects its preferred negotiating outcome in one forum of the regime complex with its action in another forum (fora), as well as the conditions shaping these ‘connections’. To do so, it employs a sequential research design utilising qualitative content analysis, qualitative comparative analysis, and process tracing. Data analysis is based on a triangulation of 53 semi-structured interviews with officials involved in the four negotiations, official documents, and press reports. The dissertation identifies four ways in which the EU utilised different fora of the regime complex to facilitate its preferred outcome in the four negotiations (connection types): employing typical multilateral negotiation activities, overcoming specific issues of the negotiations, creating political momentum, and ensuring cross-fora coordination. The analysis suggests that the EU’s use of the specific connection types is determined by the extent to which a given forum of the regime complex overlaps with the main negotiating forum as well as the EU’s internal coordination structure for each forum. Hence, the EU’s diplomacy is not only a reflection of the opportunities available to it but also its internal ability to work across its substructures and seize these opportunities. Via an intensive analysis of the EU’s diplomacy in the four negotiations, the dissertation expands the scope of the study of EU climate diplomacy while also developing an actor-agnostic framework for identifying and explaining a new type of actor behaviour within regime complexes.
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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 | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.018 | 0.020 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".