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Record W3022814492 · doi:10.26522/vp.v17i1.2473

La femme en colère : la violence de Moze de Zahia Rahmani

2020· article· fr· W3022814492 on OpenAlexvenueno aff
Brigitte Stepanov

Bibliographic record

VenueVoix Plurielles · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article aborde la question de la colère et de la violence au féminin dans Moze (2003) de Zahia Rahmani, un roman qui se penche sur l’histoire d’un harki – de même que l’Histoire des harkis – et de la vie de sa famille après son suicide. Plusieurs formes de violence – tant physiques que textuelles – y sont soulignées, ainsi que l’oscillation entre le privé et le public, le souvenir individuel et collectif, le passé et le présent, la France et l’Algérie. Je soutiens que la narratrice, la fille du harki qui donne son nom au roman, utilise la parole non seulement comme réponse à la violence coloniale, à titre de réplique enragée et violente aux injustices commises contre les harkis, mais encore comme une manière de vaincre le traumatisme de la colonisation et de faire le deuil de ce passé terni. Mots-clés : harki, Algérie, théorie postcoloniale, violence, traumatisme, narration

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)0.001
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: none
Teacher disagreement score0.086
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.006
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.068
GPT teacher head0.353
Teacher spread0.284 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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