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Record W2521432699 · doi:10.1080/09692290.2016.1224770

Negotiating Greece. Layering, insulation, and the design of adjustment programs in the Eurozone

2016· article· en· W2521432699 on OpenAlexaff
Manuela Moschella

Bibliographic record

VenueReview of International Political Economy · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsCentre for International Governance Innovation
FundersGeorgetown University
KeywordsOpposition (politics)NegotiationEconomicsRestructuringStatus quoEuropean unionPolitical economyPoliticsInternational economicsBrexitEconomic systemPolitical scienceMarket economyLawFinance

Abstract

fetched live from OpenAlex

The paper sets out to explain why the European Central Bank and the European Commission relaxed their opposition to debt restructuring and fiscal accommodation for Greece in the shift from the first to second adjustment program. Using the findings of the empirical analysis, the paper shows that EU institutions’ repositioning cannot easily be ascribed to the mechanisms that are typically at play in international negotiations, namely exogenous pressures and internalization of new beliefs through persuasion. Instead, the paper argues that a more nuanced and complete explanation of the relaxation of opposition to the change in the program strategy requires taking into account the institutional and temporal dimensions of the Troika negotiations. Specifically, the paper shows that the evolution of European actors’ preferences was shaped by the layering of new crisis management rules into the machinery of the monetary union. Layering allowed political actors in favor of the status quo achieving their preferences under changed external circumstances.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.005
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.343
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations63
Published2016
Admission routes1
Has abstractyes

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