Multilateral Development Finance in Non‐Western Thought: From Before Bretton Woods to Beyond
Bibliographic record
Abstract
ABSTRACT Recent initiatives of China and other emerging powers to create new multilateral development lending institutions (MDLIs) are often portrayed as efforts to build upon and/or reform an idea pioneered by Western officials during the Bretton Woods negotiations. However, recent literature has shown that support for MDLIs also had deeper non‐Western roots in the pre‐Bretton Woods era. What led thinkers outside the West to propose MDLIs in that earlier period? How might their ideas be relevant to current non‐Western initiatives to create new MDLIs? This article addresses these questions with a special focus on the ideas of China's Sun Yat‐sen (1866–1925) and Peru's Víctor Raúl Haya de la Torre (1895–1979). Although their intellectual journeys were quite distinct and their specific proposals differed, these two thinkers advocated the creation of MDLIs for similar reasons that stemmed from their anti‐imperialist sentiments. Their ideas find some echoes in current non‐Western initiatives.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.023 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".