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Record W2947259246 · doi:10.1111/jcms.12924

Incoherence in Regime Complexes: A Sentiment Analysis of EU‐IMF Surveillance

2019· article· en· W2947259246 on OpenAlex
Michael Breen, Dermot Hodson, Manuela Moschella

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

VenueJCMS Journal of Common Market Studies · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsCentre for International Governance Innovation
Fundersnot available
KeywordsPessimismProxy (statistics)Member statesEuropean unionFinancial crisisPolitical scienceEconomicsPower (physics)Tone (literature)International economicsMacroeconomics

Abstract

fetched live from OpenAlex

Abstract The proliferation of international institutions means that states can be subject to multiple, overlapping and potentially incoherent international obligations. The regime complexity literature draws attention to this problem but says little about its character and causes. This article investigates whether and why two key components of the international economic surveillance regime – the International Monetary Fund (IMF) and the European Union (EU) – impose conflicting obligations on the same states. Based on a comparative sentiment analysis of more than 400 surveillance documents and using differences in tone as a proxy for incoherence, our results show that the IMF was more pessimistic about member states' economic policies before the global financial crisis but less so thereafter. Our results suggest that differences in discretionary authority rather than the distribution of power drove such incoherence, with the EU's fiscal rules encouraging less pessimism before the global financial crisis and more pessimism thereafter.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.039
GPT teacher head0.303
Teacher spread0.264 · 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