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Record W6948498708 · doi:10.5281/zenodo.10658226

From Cooperative To Coercive Federalism? The Legislative Function Under Next Generation EU And The Federal Genus of Union Law

2023· article· en· W6948498708 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFederalismLegislatureLeverage (statistics)Cooperative federalismSuccessor cardinalFunction (biology)Unilateralism

Abstract

fetched live from OpenAlex

This Working Paper examines what Next Generation EU (NGEU) does to the structure of federalism in the EU. It draws a comparison between the Recovery and Resilience Facility (RRF) and conditional spending programmes in US, Australian and Canadian federalism to identify a heuristic framework for determining when funding to (Member) States crosses the line between policy leverage and a form of federal coercion. While, after the RRF, the cohesion legal basis takes on features in common with the US “general welfare clause”, the Working Paper argues that the RRF does not have an unambiguously coercive character that satisfies the definition of compulsion gleaned from comparative federal jurisprudence. With that template, the Working Paper puts forward tools to understand if the RRF and its putative “de-crisisified” successor leave sufficient policy space for Member States and their legislatures to exercise real choice regarding the acceptance of funds, based on the size, granularity and extraneousness of conditional spending.

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)0.008
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.020
Scholarly communication0.0070.009
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.052
GPT teacher head0.250
Teacher spread0.199 · 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 designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicGenomics and Phylogenetic Studies→French-language works237,207→