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Record W2336610092 · doi:10.1080/13501763.2016.1272623

Executive-legislative relations and inter-parliamentary cooperation in federal systems – lessons for the European Union

2017· article· en· W2336610092 on OpenAlexaboutno aff
Nicole Bolleyer

Bibliographic record

VenueJournal of European Public Policy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
FundersEuropean Research Council
KeywordsPolityLegislaturePolitical sciencePoliticsSeparation of powersPublic administrationParliamentMember statesEuropean unionPolitical economyState (computer science)LawSociologyEconomics

Abstract

fetched live from OpenAlex

This paper examines the claim that the fusion between executive and parliamentary majority (that marks parliamentary regimes and thus most EU member states) makes the development of a proactive collective role of national parliaments as a political force in the European multilevel system unlikely – irrespective of growing attempts to formally empower national parliaments. Conditions for inter-parliamentary activism – defined as joint parliamentary activities that aim at enhancing parliaments’ political influence or interests in a multilevel polity – are critically examined by a comparative study of the nature of inter-parliamentary activities in three federal systems whose constituent units are characterized by most different executive-legislative relations. In line with theoretical expectations, inter-parliamentary activism is strongest in the US (separation of powers) and non-existent in Canada (parliamentarism), with Switzerland located in between (separation of powers bridged by party ties). With the EU being most similar to Canada when it comes to executive-legislative relations on the ‘lower’ member-state level, the findings support those skeptical towards national parliaments’ potential to jointly become a politically active player in the EU.

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)0.009
metaresearch head score (Gemma)0.009
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: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.011
Scholarly communication0.0100.006
Open science0.0010.004
Research integrity0.0020.001
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 head0.064
GPT teacher head0.348
Teacher spread0.285 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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