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Record W4200155844 · doi:10.1111/jcms.13267

The European Semester as Goldilocks: Macroeconomic Policy Coordination and the Recovery and Resilience Facility

2021· article· en· W4200155844 on OpenAlexaff
Bart Vanhercke, Amy Verdun

Bibliographic record

VenueJCMS Journal of Common Market Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsResilience (materials science)European commissionCorporate governanceBalance (ability)Political scienceInstitutionalismPower (physics)Goldilocks principlePsychological resiliencePublic administrationPublic relationsBusinessEconomicsManagementEconomic policyPoliticsEuropean unionLawPsychology

Abstract

fetched live from OpenAlex

Abstract How and why did the European Semester end up as the main institutional vehicle of the Recovery and Resilience Facility (RRF)? To what extent did this new set‐up change the power balance among key actors (for example, financial and economic actors versus social affairs actors)? Drawing on historical institutionalism and based on 28 semi‐structured interviews and document analysis, our assessment suggests that while social actors were initially side‐lined and national executives strengthened, over time the pendulum is swinging back. The usual actors are strategically using the institutional structures of the revised Semester as a vehicle to ‘have a say’ in the RRF. Having more carrots and sticks suggests further strengthening the pivotal role of the European Commission. Yet having the option of submitting national plans gives member states options too. The EU institutional response to the Covid‐19 pandemic built on, and further cemented, the EU's socio‐economic governance architecture.

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)0.010
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.006
Scholarly communication0.0110.006
Open science0.0010.009
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.018
GPT teacher head0.318
Teacher spread0.300 · 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 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

Citations130
Published2021
Admission routes1
Has abstractyes

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Same venueJCMS Journal of Common Market StudiesSame topicEuropean Union Policy and GovernanceFrench-language works237,207