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Record W2002441173 · doi:10.7202/013347ar

Grand corps et mini-États ou l’image d’un tout ce que nous sommes en Tunisie

2006· article· fr· W2002441173 on OpenAlexaffvenue
H. Saïdi

Bibliographic record

VenueEthnologies · 2006
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesSpectaclePhilosophyPolitical science

Abstract

fetched live from OpenAlex

Cet article traite de deux questions principales : le corps et l’État. L’auteur prend le cas de figure d’un spectacle de danse qui était produit et diffusé au cours des années 1990 en Tunisie. Intitulé « Nouba », ce spectacle fournit les appuis empiriques nécessaires pour que l’idée faisant de l’État un Grand Corps et du corps un mini-État ne se limite point à la métaphore, mais s’attache plutôt à la réalité. En effet, cette idée a permis à l’auteur d’appréhender le pays et le spectacle l’un à la lumière de l’autre, tout en portant l’analyse hors des sentiers battus. Cela dit, le fait que l’article traite de la question du corps dans une société arabo-musulmane ne l’implique pas automatiquement dans la sphère des études orientalistes ou islamologiques. Autrement dit, ce n’est pas de l’interdit que l’on discute dans ce texte, mais plutôt de l’inter-dit.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.088
GPT teacher head0.378
Teacher spread0.290 · 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 teacher head, not a consensus.

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
Published2006
Admission routes2
Has abstractyes

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