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Governance and State Power: A Network Analysis of European Security

2010· article· en· W1866407574 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJCMS Journal of Common Market Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsCorporate governanceInstitutionalisationState (computer science)Power (physics)Political scienceNetwork governanceSocial network analysisMulti-level governancePublic administrationEconomic systemSociologyEconomicsLawManagement

Abstract

fetched live from OpenAlex

Abstract A growing number of scholars argue that the development of the common security and defence policy (CSDP) should be analysed as the institutionalization of a system of security governance. Although governance approaches carry the promise of a sophisticated, empirically grounded picture of CSDP, they have been criticized for their lack of attention to power. This is because governance approaches focus on institutional rules and ideas rather than the social structure that underpins them. To refine the notion of security governance, this article analyses co‐operation patterns through social network analysis. Confirming the governance image, it maps out a complex constellation of CSDP actors that features cross‐border and cross‐level ties between different national and EU policy actors. It is also found, however, that CSDP is dominated by a handful of traditional state actors – in particular, Brussels‐based national ambassadors – who retain strategic positions vis‐à‐vis weaker supranational and non‐state actors. These actors are not giving up on state power, but reconstituting it at the supranational level.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.313
Teacher spread0.297 · 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