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Record W4300043363 · doi:10.3917/etan.752.0192

Unruly Stories: Opening up to History in Helon Habila’s Travelers

2022· article· fr· W4300043363 on OpenAlexaff
Eleni Coundouriotis

Bibliographic record

VenueÉtudes anglaises · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicDiaspora, migration, transnational identity
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Dans son roman Travelers , Helon Habila propose le terme de « voyageurs » au lieu de réfugié, demandeur d’asile, migrant ou exilé, afin de se désengager des récits qui accompagnent habituellement ces termes. Constatant que les identités créées par la crise migratoire européenne des années 2010 ont occulté les raisons de la mobilité accrue des Africains durant cette période, Habila met en scène dans son roman des rencontres qui renouvellent sans cesse les possibilités pour les voyageurs de raconter les raisons de leur fuite. Les caractéristiques formelles du roman – récits imbriqués, temporalités multiples et tournants imprévisibles – renforcent son éclairage historique en invitant à examiner de plus près la relation entre migration et récit de vie. Le protagoniste anonyme est investi dans l’étude formelle de l’histoire, mais il vit aussi l’histoire alors qu’il se laisse envahir par l’expérience des réfugiés, renonçant à la sécurité de son propre statut légal. Habila met en évidence le potentiel transformateur du récit mais il aborde également de manière ironique les pouvoirs de transformation supposés de l’identification empathique. En proposant un retour en Afrique et un réengagement dans la vie ordinaire du continent, Habila utilise la fin du roman pour proposer un geste décolonial : ouvrir l’avenir en tournant le dos à l’Europe.

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)0.002
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0230.022
Scholarly communication0.0090.009
Open science0.0010.009
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0110.001

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 head0.074
GPT teacher head0.315
Teacher spread0.241 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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