Fragmented multilateralism and international institutions: between complexities and challenges
Bibliographic record
Abstract
This special issue examines the impact of the fragmentation of multilateralism on Informal Internatİonal Governmental Organİsatİons (IIGOs) and Formal Internatİonal Governmental Organİsatİons (FIGOs) through the lens of Global North–Global South relations. In the first part, a short literature review on multilateralism and its crisis is presented. In the second part of our cluster, focusing on ‘Multilateralism and International Institutions’, the authors explore how China and India contest the current form and meaning of multilateralism, and how US policies towards institutions like the United Nations (UN) shift with presidential politics, as well as the roles of United Nations Conference on Trade and Developmen (UNCTAD) and The United Nations Commission on International Trade Law (UNCITRAL). The third part, on ‘Multilateralism, Informality and IOs’, addresses the intersection of informal governance, multilateralism and the Global South. It includes studies on the European Union’s (EU’s) informal engagement with IIGOs, states’ use of ad hoc coalitions, hybrid practices in The Association of Southeast Asian Nations (ASEAN), the Quad, and the China–Japan–Korea Trilateral Summit. The fourth and final part, on ‘Geopolitics, Multilateralism and International organisations (IOs)’, explores the interplay among geopolitics, multilateralism and IOs and engages with key themes such as the EU’s challenges in FIGOs led by authoritarian regimes favouring instrumental over normative cooperation, and the early emergence of Latin American IIGOs in the nineteenth century, predating formal IOs.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".