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Record W1981641851 · doi:10.1111/1468-5965.00207

Policy Legitimacy and Institutional Design: Comparative Lessons for theEuropean Union

2000· article· en· W1981641851 on OpenAlexaboutno aff
David McKay

Bibliographic record

VenueJCMS Journal of Common Market Studies · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsLegitimacyDecentralizationContext (archaeology)LegislatureAutonomyEuropean unionState (computer science)Political scienceDemocratic deficitPublic administrationPoliticsDemocracyFiscal unionEconomic systemEconomicsPolitical economyFiscal policyEconomic policyMacroeconomicsLaw

Abstract

fetched live from OpenAlex

Research on the democratic deficit in the European Union (EU) tends to focus on general questions of institutional design rather than the link between institutions and specific policy responsibilities. This article argues that, following EMU, a high degree of fiscal centralization is not tenable given theabsence of EU‐wide citizen support for a greatly enhanced central role and European political parties operating in a genuine European legislature. Given this, it is appropriate to examine fiscal relations in existing federations to discover which, if any, approximates to the likely post‐EMU pattern in the EU. The experience of five federations – Australia, Canada the US, Germany and Switzerland suggests that most can be learnt from the Swiss model which is characterized by a high degree of vertical fiscal autonomy, and state (cantonal) interpenetration of national decision‐making. The article concludes that, while Switzerland cannot serve as a model for the EU, the Swiss experience does show that a modern industrial state can successfully operate in the context of a high degree of fiscal decentralization.

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)0.013
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0040.016
Scholarly communication0.0120.009
Open science0.0010.006
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.157
GPT teacher head0.437
Teacher spread0.280 · 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 designQualitative
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

Citations37
Published2000
Admission routes1
Has abstractyes

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Same venueJCMS Journal of Common Market StudiesSame topicPolitical Systems and GovernanceFrench-language works237,207