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Record W7002069682

L'œuvre Maman de Louise Bourgeois: vecteur de compréhension de la relation entre l'institution muséale et l’espace public

2023· dissertation· fr· W7002069682 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2023
Typedissertation
Languagefr
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsPublicsBourgeoisiePublic investmentHistorical heritage
DOInot available

Abstract

fetched live from OpenAlex

De Tokyo à Ottawa en passant par Bilbao, le lien que le public tisse avec l’œuvre Maman (1999) de Louise Bourgeois se forge dans l’espace interstitiel situé entre la rue et l’institution muséale. Les esplanades publiques du Musée des beaux-arts du Canada à Ottawa et du Musée Guggenheim Bilbao dans le Pays basque espagnol permettent d’analyser comment le passage entre les artères urbaines et l’institution muséale possède des fonctions qui peuvent être décodées par l’entremise de l’étude de Maman. Ainsi, pourquoi faut-il considérer l'œuvre Maman de Louise Bourgeois comme un outil de capitalisation permettant aux musées qui l’accueillent d’exploiter leur connexion physique à l’espace public, de disséquer toutes les facettes de la relation qu’ils entretiennent à leurs publics et de préserver leur positionnalité au sein de l’écosystème urbain? \n \nCette thèse utilise ces deux expositions publiques permanentes de l'œuvre de Bourgeois afin de sonder l'impact de la sculpture sur les comportements des utilisateurs de la place publique lorsqu’en présence d’un musée côtoyé dans l'environnement urbain. Plus particulièrement, elle analyse les points d’intersection physiques entre l’œuvre et les plazas muséales en relevant cinq facteurs qui permettent à ces institutions de contrôler et pérenniser leur image publique grâce aux choix curatoriaux qui caractérisent les expositions publiques de Maman.

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)0.001
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: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.891

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.011
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.036
GPT teacher head0.279
Teacher spread0.243 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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