The United Arab Emirates and the New Development Bank: Mutual interests and <scp>first‐mover</scp> advantages
Bibliographic record
Abstract
Abstract The United Arab Emirates (UAE) joined the BRICS‐led New Development Bank (NDB) as part of its first expansion in terms of membership. Questions regarding the interests and rationale of the UAE in joining the Bank, on the one hand, and the NDB's logic in granting membership to the UAE, on the other, immediately jump out. This article sheds light on the BRICS' cautious move away from exceptionality via the expanded NDB in the context of its membership criteria and approach. It does so by also highlighting the UAE's exceptionality, with a focus on the combination of fiscal resources and strategic geography, in the context of shifting global distributions of power. It finds that the UAE's membership in the NDB dovetails with its memberships in other MDBs, which, in turn, are part of the country's ambition to be seen as a globally influential actor. In turn, the NDB was attracted to the UAE fiscal acumen, credit rating and its carefully cultivated culture of cutting‐edge, sustainable, infrastructure and connectivity projects, as well as innovation.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".