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Record W4360862833 · doi:10.4000/brussels.6759

Capitales fédérales et institutions culturelles nationales. Leçons pour Bruxelles des exemples de Berlin, Brasilia, Canberra et Ottawa

2022· article· fr· W4360862833 on OpenAlexaboutno aff
Arnaud Bouten, Karel Reybrouck

Bibliographic record

VenueBrussels Studies · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Compte tenu de l’évolution constante de la Belgique vers une plus grande décentralisation des compétences, le statut futur des institutions culturelles fédérales à Bruxelles demeure incertain. Afin d’élargir le champ du débat politique, le présent article présente une comparaison des configurations institutionnelles des institutions culturelles nationales dans différentes capitales fédérales. Les cas de Berlin, Brasília, Canberra, Ottawa et Bruxelles sont examinés, l’accent étant mis sur la répartition constitutionnelle des compétences et sur les mécanismes de coopération entre les niveaux de gouvernement. Cet état des lieux montre que le gouvernement fédéral joue invariablement un rôle dans l’administration des institutions culturelles nationales dans les différentes capitales. En outre, dans la plupart des capitales, des mécanismes de coopération culturelle sont mis en place pour coordonner l’action fédérale et celle des entités fédérées. Sur ce dernier point, il semble que des améliorations soient possibles à Bruxelles.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.755
Threshold uncertainty score0.487

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.007
Scholarly communication0.0050.002
Open science0.0000.001
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 head0.110
GPT teacher head0.387
Teacher spread0.277 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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