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Enjeux politiques de la création/rénovation des musées nationaux de société. Étude comparative : le Musée de la civilisation de Québec, le Musée des civilisations de l'Europe et de la Méditerranée (MuCEM) de Marseille et le Tropenmuseum d'Amsterdam

2024· dissertation· W7151755117 on OpenAlexaboutno aff
Rebeca Alfonso Romero

Bibliographic record

Venuenot available
Typedissertation
Language
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsCivilizationNational identityContext (archaeology)National state

Abstract

fetched live from OpenAlex

Le musée national est défini comme pilier de la construction de l'imaginaire national de l'État moderne. Parmi ces musées, les musées de société abritent des collections (ethnologiques, historiques, d'art populaire) et élaborent des discours qui sont le reflet des valeurs légitimes de la vie en société. Depuis les années 1990, un phénomène de création/rénovation de musées se développe dans le cadre de la haute mondialisation et de l'évolution administrative et politique des États. Notre recherche analyse trois processus récents de création/ rénovation de musées nationaux de société : le Musée de la civilisation de Québec, Canada ; le Musée des civilisations de l'Europe et de la Méditerranée (MuCEM) de Marseille, France ; et le Tropenmuseum d'Amsterdam, Pays-Bas. Nous comparons ces processus en nous appuyant sur l'étude des archives nationales et selon quatre axes : historique, attributs politiques, dynamiques spatiales, rénovation/création. Nous proposons trois nouvelles approches de la construction de l'imaginaire national : patrimonial, stratégique ou symbolique.

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)0.004
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.478

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.007
Science and technology studies0.0130.020
Scholarly communication0.0090.005
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.078
GPT teacher head0.364
Teacher spread0.287 · 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
Published2024
Admission routes1
Has abstractyes

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