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Record W2777935986 · doi:10.30950/jcer.v13i4.861

Diversified Economic Governance in a Multi-Speed Europe: a Buffer against Political Fragmentation?

2017· article· en· W2777935986 on OpenAlexaff
Constantinos Yanniris

Bibliographic record

VenueJournal of Contemporary European Research · 2017
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal Financial Crisis and Policies
Canadian institutionsMcGill University
Fundersnot available
KeywordsRealpolitikPoliticsBrexitEuropean unionPolitical unionFlexibility (engineering)European debt crisisCorporate governanceEuropean integrationPolitical economyEconomic and monetary unionCurrencyEconomic systemEconomicsPolitical scienceInternational economicsFinanceMacroeconomicsLaw

Abstract

fetched live from OpenAlex

As it turns 60, the European Union appears engulfed in a crisis. In response to this, political actors have recently advocated a multi-speed Europe. A metaphor for the central idea is the integration highway: since member states are already moving with different speeds, countries need to be separated into different lanes to avoid a major accident. Although the idea of a multi-speed Europe has been criticised as an abatement of the initial dream of simultaneous European integration, this commentary views it as a realpolitik that will allow for greater flexibility in decision-making at times when a fast response to financial, humanitarian and security challenges is imperative. To illustrate this, a scenario is presented on how a multi-speed Europe policy can be applied within the Eurozone to shape two parallel common currency zones. A meticulous application of the multi-speed Europe principle to the Eurozone could address the shortcomings of the initial monetary integration plan and protect the long-term interests of the continent and beyond.

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)0.004
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.226
GPT teacher head0.373
Teacher spread0.147 · 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.

Study designObservational
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

Citations2
Published2017
Admission routes1
Has abstractyes

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