Architecture of the Global Financial System: Transformation vs Stability?
Bibliographic record
Abstract
The paper discusses current development of the world financial system through the processes of transforming its architecture or stabilizing the existing model. The study is based on the data on international trade and international reserves of different countries of the world (both developing and developed), as well as on the structure of financial claims (assets) and obligations (liabilities) to external counterparties, emphasizing two key associations of countries – the five BRICS economies and the Group of Seven. It is shown that developing countries are the key initiators of transformation processes of the global financial system (including de-dollarization of international settlements and the shift to broader use of national currencies in cross-border payments, as well as increasing the share of monetary gold in their international reserves). At the same time, developed countries are rather traditional in their currency ‘preferences’. Such adherence emerges through far more pervasive dependence of the UK, Italy, Canada, Germany, France, and Japan (which constitute six of the Group of Seven countries) on the US throughout the last 15 years following the consequences of the 2008–2009 crisis, the European debt crisis, the COVID-19 pandemic, and growing geopolitical tensions in 2022–2024. Such increased dependence in developed countries does not simply prevent them from moving away from the US dollar in settlements, but, on the contrary, increases its importance there as a means of payment, accumulation, and a way to hedge risks. The conducted analysis has revealed multidirectional trends in the development of the financial systems of both developed and developing countries. The result of the global interaction among financial systems of different countries depends on a variety of factors and can contribute both to the transformation of the global financial system or to the sustenance of the current model
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".