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Bureaucracy and place: expertise in the European Quarter

2011· article· en· W2009746437 on OpenAlexfundaboutno aff
Merje Kuus

Bibliographic record

VenueGlobal Networks · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGeopoliticsBureaucracyScholarshipContext (archaeology)Political sciencePoliticsEuropean unionPower (physics)State (computer science)SociologyPolitical economyQuarter (Canadian coin)Public administrationLawGeographyEconomicsInternational trade

Abstract

fetched live from OpenAlex

Abstract Bureaucratic structures and procedures are an integral part of the production of political space today. Analyses of geopolitical practices must therefore unpack the bureaucratic context in which these practices unfold on a daily basis. This is particularly important if we wish to understand transnational processes that operate at scales and in contexts other than the familiar contours of the nation‐state. In this article, I focus on one bureaucratic centre of geopolitics – the European Quarter in Brussels, Belgium, the institutional centre of the European Union. Drawing from scholarship on geopolitics and policy‐making, as well as primary interview material from field research in Brussels, I make two related points – (1) that we need detailed close‐up studies of the bureaucratic settings of contemporary geopolitics, and (2) that we must carefully situate such settings in their place‐specific contexts to reveal dynamics that remain unnoticed from afar. Empirically, the article contributes to the interdisciplinary scholarship on the EU as a transnational power centre of global importance. Theoretically, it seeks to improve our understanding of geopolitics as a bureaucratic and material practice.

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)0.005
metaresearch head score (Gemma)0.011
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0050.014
Scholarly communication0.0080.005
Open science0.0010.008
Research integrity0.0010.001
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 head0.028
GPT teacher head0.279
Teacher spread0.251 · 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

Citations29
Published2011
Admission routes2
Has abstractyes

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