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Les équipements culturels et la pratique culturelle dans la ville québécoise

2004· article· fr· W2318033698 on OpenAlexaffvenue
Brigitte Ricard, Rosaire Garon

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2004
Typearticle
Languagefr
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsMinistère de la Culture et des Communications
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La culture est une composante de la fonction urbaine. La ville rassemble les organismes et les infrastructures nécessaires pour dispenser ses services culturels aux citoyens, façonnant ainsi leurs agissements. Cependant, toutes les villes ne disposent pas du même niveau de ressources et toutes les populations urbaines n’adoptent pas les mêmes comportements culturels. Partant de l’exemple des grandes villes québécoises, les auteurs explorent quelques hypothèses en vue de comprendre la variabilité des pratiques culturelles en milieu urbain. Délaissant une approche explicative par la composition sociodémographique des populations, ils s’appuient plutôt sur une hypothèse relative à l’offre de services culturels. La structuration différente des équipements culturels des villes permet de comprendre pourquoi les populations urbaines affichent des pratiques d’intensité variable. Elle aide également à mieux saisir l’attraction particulière ou plus forte qu’elles exercent sur leur entourage. Toutefois, elle n’est pas complètement satisfaisante et la morphologie des villes, qui permet aux villes d’assumer plus ou moins adéquatement leurs fonctions centrales, pourrait être un autre élément à considérer.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.197

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.030
GPT teacher head0.330
Teacher spread0.300 · 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 designObservational
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

Citations1
Published2004
Admission routes2
Has abstractyes

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