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Record W1581715893

Racisme(s) ? Une étude rhétorique critique de la polémique sur le racisme anti-Blancs en France

2007· article· fr· W1581715893 on OpenAlexaff
Damien Charrieras

Bibliographic record

VenueCommposite · 2007
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophyEthnologyArtSociology
DOInot available

Abstract

fetched live from OpenAlex

Le 25 mars 2005 a ete lance en France un appel contre le racisme anti-Blancs pour denoncer des agressions dont ont ete victimes de jeunes lyceens, en marge d'une manifestation lyceenne s'etant deroulee le 8 mars 2005 a Paris. Cet appel provient d'un mouvement de jeunesse sioniste de gauche, Hachomer Hatza'ir - sur le site duquel l'appel a ete publie - et de Radio Shalom, une radio destinee a la communaute juive de France. Le but de notre essai est de reconstruire, a partir de l'appel contre le racisme anti-Blancs du 25 mars et de ses fragments, un texte suitable for criticism, suivant la formule du rhetoricien critique americain Michael Calvin McGee ; un texte qui permette a notre audience de developper son esprit critique, habituellement emousse par la dispersion du sens et le non-dit (les fragments omis) des textes qui lui sont presentes. Nous chercherons a mettre au jour les pretentions a la validite du texte pour en analyser le contenu a la lumiere de sa genealogie (incomplete), du contexte qui accompagne sa stabilisation dans l'espace public et de sa dispersion immediate. Nous verrons comment la mise en avant de la notion de racisme anti-Blancs par l'appel du 25 mars informe une rearticulation de la notion de racisme en France.

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)0.006
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.069
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0180.023
Scholarly communication0.0130.005
Open science0.0010.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.283
Teacher spread0.273 · 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
Published2007
Admission routes1
Has abstractyes

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