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Olivia Elkaim, Le tailleur de Relizane

2020· article· fr· W3108524446 on OpenAlexaff
Mustapha Harzoune

Bibliographic record

VenueHommes & migrations · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Née à Téhéran en 1966, Ghazel quitte l’Iran en 1986 pour venir étudier en France. « Nomade hybride » comme elle s’est longtemps qualifiée, elle se considère davantage aujourd’hui comme une artiste en « transit permanent ». Son œuvre examine les questions de déracinement, d’appartenance et d’hybridité. Les notions de migrations contemporaines, de circulations, mais aussi la guerre et ses effets irriguent sa démarche. En « suspension entre deux mondes », chacun « tenant lieu de référence et de maison », Ghazel explore son identité multiple tout en réinventant son univers. « Je suis une “étrangère” dans ces deux mondes – l’Occident et l’Iran – et c’est mon monde à moi que je révèle. » 1. Ghazel a participé à de nombreuses manifestations internationales telles que la 50e Biennale de Venise (2003), la 8e Biennale de La Havane (2003), la 3e Biennale de Tirana (2005), la 7e Biennale de Sharjah (2005), la 15e Biennale de Sydney (2006), la 14e Biennale Donna à Ferrare (2010) et la 13e Biennale de La Havane (2019). Son travail est présent dans de nombreuses collections publiques : Musée national d’art moderne, Centre Pompidou, Paris (France), Museum Moderner Kunst Stiftung Ludwig (Mumok), Vienne (Autriche), Musée national de l’histoire de l’immigration (MNHI), Paris (France). En 2018, elle est nommée au grade de Chevalier de l’ordre des Arts et des Lettres par le ministre de la Culture français. Ghazel choisit le Musée national de l’histoire de l’immigration, Palais de la Porte Dorée, pour recevoir sa décoration.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0060.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.003

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 head0.114
GPT teacher head0.367
Teacher spread0.253 · 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
Published2020
Admission routes1
Has abstractyes

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