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Record W6981948580

French speaking theatres

2002· other· fr· W6981948580 on OpenAlexaboutno aff

Bibliographic record

VenueOpenGrey (Institut de l'Information Scientifique et Technique) · 2002
Typeother
Languagefr
FieldArts and Humanities
TopicHistory of Science and Natural History
Canadian institutionsnot available
Fundersnot available
KeywordsSubversionFrenchPeriod (music)
DOInot available

Abstract

fetched live from OpenAlex

La francophonie concerne plus de 200 millions de personnes qui parlent le français à travers le monde. Depuis les années 60, de nombreux théâtres en français sont apparus. Ils sont porteurs d'une certaine subversion issue de la colonisation en Afrique subsaharienne, au Maghreb, mais aussi au Québec et dans certaines Départements Français d'Outre-Mer comme les Antilles ou La Réunion. Cette subversion est le dénominateur commun de l'ensemble des théâtres en français. Comment d'un pays à l'autre, les pièces se répondent-elles ? Tout théâtre est un lieu subversif par essence mais en s'appropriant le politique et l'Histoire, les théâtres d'expression française revisitent ces notions. Les femmes, les fous et les fantômes communs à la plupart des théâtres deviennent des outils de cette même subversion donnant d'autres références à ces personnages. Dans la dernière partie, nous constaterons comment les théâtres en français font éclater à la fois les cadres comme l'espace et le temps mais aussi les modèles théâtraux tels que le tragique et la langue, jouant à nouveau de cette même posture subversive.

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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.179
Threshold uncertainty score0.355

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0120.004
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0850.016

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 head0.025
GPT teacher head0.245
Teacher spread0.221 · 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
GenreOther

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
Published2002
Admission routes1
Has abstractyes

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