Legitimacy in an Era of Fragmentation: The Case of Global Climate Governance
Bibliographic record
Abstract
Studies grounded in regime theory have examined the effectiveness of “minilateral” climate change forums that have emerged outside of the UN climate process. However, there are no detailed studies of the legitimacy of these forums or of the impacts of their legitimacy on effectiveness and governance potential. Adopting the lens of legitimacy, we analyze the reasons for the formation of minilateral climate change forums and their recent role in global climate governance. We use Karlsson-Vinkhuyzen and Vihma's analytical framework for international institutions to examine three minilateral climate forums: the Asia-Pacific Partnership, the Major Economies Meetings, and the G8 climate process. These forums have significant deficits in their source-based, process-based, and outcome-based legitimacy, particularly when compared to the United Nations Framework Convention on Climate Change. If assessed purely on grounds of effectiveness, the minilateral forums might be easily dismissed as peripheral to the UN climate process. However, they play important roles by providing sites for powerful countries to shape the assumptions and expectations of global climate governance. Thus, the observed institutional fragmentation allows key states to use minilateral forums to shape the architecture of global climate governance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.016 | 0.053 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".