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Record W3107736406

Vers un ethnotext transatlantique : kabyle algérien ; Rifain et Maghrebi marocains ; Choctaw américain et M’kmaq canadien dans les écrits autobiographiques d’Afrique du Nord et d’Amérique du Nord

2019· article· fr· W3107736406 on OpenAlexaboutno aff
Chérif Sadaoui

Bibliographic record

Venuetheses.fr (ABES) · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicLinguistic and Sociocultural Studies
Canadian institutionsnot available
FundersUniversity of Tsukuba
KeywordsHumanitiesArtEthnologyHistory
DOInot available

Abstract

fetched live from OpenAlex

Cette thèse explore la notion de l’ethnotext comme stratégie de résistance à la domination linguistique. Cette notion sera étudiée en relation avec trois formes de domination linguistique: la colonisation française en Algérie (1830-1962) et le protectorat français et espagnole au Maroc (1912-1956) ; les politiques linguistiques post-indépendances appliquées par ces deux Etats nation ; l’installation européenne au Canada et aux Etats Unis D’Amérique et les conséquences de ses politiques linguistiques néocoloniales sur les langues amérindiennes telles que le M’ikmaq (au Canada) et le Choctaw (USA). L’étude sera menée en s’appuyant sur un corpus de quatre romans autobiographiques, représentatifs des cultures berbères (kabyle et rifain) ainsi qu’amérindiennes (M’ikmaq et Choctaw). L’ethnotext kabyle sera étudié dans le roman de Mouloud Feraoun Le fils du pauvre (1950) ; le Rifian sera étudié dans le roman de Mohamed Choukri Le pain nu (1973) ; le M’ikmaq sera étudié dans le roman de Rita Joe : Song of Rita Joe : Autobiography of a M’ikmaq Poet (1996) et leChoctaw sera étudié dans le roman de Rilla Askew The Mercy Seat (1997). Cette étude comparative a pour objectif de comparer ces quatre cas de résistance linguistique pour chercher leurs points communs, leur ressemblances stratégiques et culturelles afin d’établir la dimension transatlantique de l’ethnotext.

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)0.004
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 score0.812
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.282
Teacher spread0.259 · 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
Published2019
Admission routes1
Has abstractyes

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