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Record W2005545713 · doi:10.1556/acr.3.2002.2.2

The Stakes of Translation in Literary Fields

2002· article· en· W2005545713 on OpenAlexaff
Jean-Marc Gouanvic

Bibliographic record

VenueAcross Languages and Cultures · 2002
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsConcordia University
Fundersnot available
KeywordsHabitusHighbrowHegemonyTranslation studiesField (mathematics)Power (physics)SociologyGlobalizationLiterary scienceLiterary criticismEpistemologyAestheticsLiteratureSocial sciencePolitical scienceLawPoliticsArtPhilosophyCultural capital

Abstract

fetched live from OpenAlex

This article proposes to examine the stakes of translation in literary texts. Inspired by Pierre Bourdieu's theory of culture, it uses the notions of habitus, field and illusio in the framework of the translation of American literature in post-WWII France. After a short definition of what a field is for Bourdieu, we analyse the power of literary translation during the period. As it is based on the relationship between the habitus of the translator and a field, the translation is endowed with a power which is not stated as such and which relies on the exercise of legitimate violence from dominants, i.e., a violence that is not known as violence, a violence that is tacitly recognised. Thus, American literature imposes in France under the form of non-canonical genres such as Science Fiction and the Série noire, but also highbrow literature, the translation of which has begun before WWII. The article closes on the stakes of Worldwide globalisation: the imposition of literary illusio , that is, the imposition of Western hegemony, on an overall scale.

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)0.045
metaresearch head score (Gemma)0.079
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: none
Teacher disagreement score0.045
Threshold uncertainty score0.240

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.079
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0250.116
Scholarly communication0.0350.040
Open science0.0020.018
Research integrity0.0070.011
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 head0.044
GPT teacher head0.319
Teacher spread0.275 · 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

Citations83
Published2002
Admission routes1
Has abstractyes

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