On the contradictions of the New International Financial Architecture: Another procrustean bed for emerging markets?
Bibliographic record
Abstract
The New International Financial Architecture (NIFA) was created by powerful G-7 countries in response to the growing volatility in the developing world. Some key components of the NIFA include: the G-20, the Financial Stability Forum and the Reports on Observance of Standards and Codes, the latter involving areas such as corporate governance. The aim of this article is to address some important yet largely neglected questions. Why the new building? Who benefits from this construction? Unlike most accounts of the NIFA, the following analysis does not remain focused on its institutional terrain; but instead draws linkages between these structures and the paradoxes inherent in global capitalism. One such contradiction is the constant promotion of financial liberalisation in emerging markets by US-led international financial institutions (IFIs), on the one hand, and the frequency of financial crises in the developing world, on the other. The article suggests that the NIFA is an attempt to strengthen (stabilise and legitimate) the scaffolding of the existing imperative of free capital mobility.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.031 |
| Scholarly communication | 0.014 | 0.026 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".