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Record W3124735550

Between Efficiency and Sovereignty: Transnational Actors, the European Union, and the Regulation of Bankruptcy

2011· article· en· W3124735550 on OpenAlexaff
Francesco Duina

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLegislatureSovereigntyPolitical scienceEuropean unionMember statesPublic administrationLawLaw and economicsInternational tradeBusinessSociologyPolitics
DOInot available

Abstract

fetched live from OpenAlex

Scholars and observers alike agree that the European Union has weakened national parliaments. This article posits that such a view, while generally accurate, ignores ways in which the EU has helped national parliaments in their function as regulators of society. It identifies two key mechanisms: precedent setting and policy transfer. First, the EU has produced laws on topics considered beyond the traditional remit of national parliaments.The EU’s intervention has justified the production of unprecedented domestic laws that go well beyond the incorporation of EU principles. This has expanded the legislative reach of national parliaments. The article considers the experiences of Italy and The Netherlands in the area of antitrust. Second, the EU has fostered an environment conducive to cross-national lesson drawing. The resulting knowledge has helped the design of more effective domestic legislative frameworks. This has confirmed the viability of national parliaments as regulatory institutions. The article examines the Open Method of Co-ordination and its application to the areas of employment and social inclusion. It concludes with a discussion of parliaments in future Member States and in Mercosur.I

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)0.012
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0070.044
Scholarly communication0.0190.013
Open science0.0010.008
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.264
Teacher spread0.243 · 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 designNot applicable
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

Citations0
Published2011
Admission routes1
Has abstractyes

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