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Record W4414074277 · doi:10.1080/09692290.2025.2553558

Layering of informal organisations in international regimes: the G20 Common Framework and the sovereign debt regime

2025· article· en· W4414074277 on OpenAlexfundno aff
Isabel Rodriguez-Toribio, Alexandra O. Zeitz

Bibliographic record

VenueReview of International Political Economy · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSovereigntySovereign debtLayeringDebtSovereign stateSustainability

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.317
Teacher spread0.306 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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