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Record W4318071529 · doi:10.5206/mf.v8i1.15887

Re/flux migratoire : une lecture sémiotique de How the García Girls Lost Their Accents de Julia Alvarez

2023· article· fr· W4318071529 on OpenAlexvenueno aff
Daniel Tia

Bibliographic record

VenueMouvances Francophones · 2023
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtEthnologyPhilosophySociology

Abstract

fetched live from OpenAlex

L’Amérique a été peuplée par vagues migratoires. Constituée originellement de tribus amérindiennes, son caractère identitaire homogène a, au fil des années, fait place à l’hétérogénéité culturelle. Si les raisons de ce flux migratoire restent variées, il faut tout de même admettre qu’il a fait éclore une dynamique culturelle que la littérature migrante hispano-américaine promeut comme modèle. Dans How the García Girls Lost Their Accents (1991) de Julia Alvarez, la société américaine est dépeinte comme un espace de refuge pour une famille dominicaine forcée à l’exil. Au-delà de l’hospitalité apparente offerte à cette famille, ses membres doivent faire face à des difficultés d’adaptation et d’intégration qui sont l’apanage des exilés. Mieux, le contact culturel qui advient dans ce contexte, s’accompagne d’une altération et d’un enrichissement culturels pourvoyeurs de significativité qu’il est besoin d’interroger sous l’angle de la sémiotique de la culture. À cet effet, deux « points-valeurs » sont considérés, à savoir l’épreuve de l’exil et la médiation culturelle.

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)0.003
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0110.008
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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
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
Published2023
Admission routes1
Has abstractyes

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