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Record W2996826305 · doi:10.17323/1996-7845-2019-02-04

Causes of G20 Compliance: Institutionalization, Hegemony, Reciprocity or Clubs

2019· article· en· W2996826305 on OpenAlex
John Kirton, Alisa Nikolaeva

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Organisations Research Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInstitutionalisationHegemonyReciprocity (cultural anthropology)Compliance (psychology)Political scienceSociologySocial sciencePsychologySocial psychologyPolitics

Abstract

fetched live from OpenAlex

In recent years, multilateralism has faced significant challenges.The rise of populist sentiment in western countries, trade wars and now slowing economic growth have undermined trust in multilateral institutions including those of a plurilateral summit form.The Group of Twenty (G20) often faces criticism for its ineffective problem-solving and members' poor compliance with their summit commitments.Yet evidence from the G20 Research Group shows that G20 members do comply solidly with the commitments they make at one summit before the next one takes place.Some summits and subjects have secured higher compliance than others.Understanding what causes compliance and how it can be improved is essential for improving G20 effectiveness, credibility and even its future.This study offers an exploratory quantitative analysis of performance at G20 summits.It relies on established conceptual frameworks and presents a descriptive inferential argument.Compliance coincides with, and thus might be improved by, making more summit commitments, holding ministerial meetings and using specific catalysts in the commitments, given the prevailing reciprocity in compliance among members rather than a single dominant actor such as the U.S. or China setting the pace.

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.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.001

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.

Opus teacher head0.218
GPT teacher head0.486
Teacher spread0.268 · 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