Layering of informal organisations in international regimes: the G20 Common Framework and the sovereign debt regime
Bibliographic record
Abstract
Given that informal organisations are thought to be easy to reform, why do states sometimes choose to create new informal institution rather than reforming existing ones? We argue states may introduce new informal layers to international regimes when the leading international organisation, even if still largely informal, becomes increasingly institutionalised, making it difficult to reform and integrate new members with diverse preferences. Further, we suggest the impact of new informal institutions on cooperation depends on the extent to which they create tensions with existing rules in the regime. We focus on the sovereign debt regime, which saw the introduction in November 2020 of the Common Framework for Debt Treatments, a new informal institution within the G20. We demonstrate that states created the Common Framework partly in response to the institutionalisation of the Paris Club, which made it more difficult to integrate China. We examine the impact of the Common Framework by comparing creditor coordination in Zambia and Sri Lanka, with only Zambia eligible for the Common Framework. This comparison reveals greater creditor coordination in Zambia than Sri Lanka, though the tensions introduced by the Common Framework nonetheless undermined the speed and quality of cooperation.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.022 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| 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".