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Record W2321075854 · doi:10.18192/clg-cgl.v2i2.143

Aire métropolitaine et grand événementiel: Une conscientisation différenciée et progressive du territoire. Étude de cas de Lille 2004, Capitale européenne de la Culture

2010· article· en· W2321075854 on OpenAlexvenueno aff
Divya Leducq

Bibliographic record

VenueCulture and Local Governance · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaContext (archaeology)Political sciencePopulationPoliticsGeographyConstitutionEconomyHumanitiesSociologyDemography

Abstract

fetched live from OpenAlex

Within the globalization of the economy, the formalization of the metropolitan areas limits depends on the political association due to the regional context. Behind the importance of the cooperation agreement between urban areas, to ensure that the territory is reaching a critical weight to compete with other cities at the European scale, it appears as crucial that the population living within this area become aware of the new space coming out, which doesn't match with the traditional political and administrative borders. This concern can pass by the cultural or sportive event for a couple of days to several months. What is the prevalence of a mega-event on the construction of a metropolitan area? Which kind of sustainable consciousness of the metropolitan city can be done by a short-lived event? Will this heedfulness be uniform and the same everywhere within the territory: should it be different according to institutional actors and civil society? The case study of Lille 2004, European Capital of Culture allows us to highlight the evolutions giving by this kind of flagship event for the constitution and the consciousness of the metropolitan region of Lille.

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)0.003
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 score0.352
Threshold uncertainty score0.699

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.007
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.007
GPT teacher head0.263
Teacher spread0.257 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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