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Record W3048643449 · doi:10.21992/tc29496

New Perspectives on Retranslation: The Case of Iran

2020· article· en· W3048643449 on OpenAlexvenueno aff
Samira Saeedi

Bibliographic record

VenueTranscUlturAl A Journal of Translation and Cultural Studies · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
FundersUniversity of Melbourne
KeywordsAmateurNovellaPersianGeorge (robot)SociologyTranslation studiesHistoryLiteratureSocial scienceMedia studiesLawArtPolitical scienceLinguisticsPhilosophyArt history

Abstract

fetched live from OpenAlex

This paper examines the social aspects of retranslation in contemporary Iran. Foreign classics and award-winning literary books have attracted multiple translations into Persian within a short period of time. For instance, George Orwell’s novella, Animal Farm, has received more than one hundred retranslations in the last 40 years. The aim of this paper is to investigate possible reasons for such an unusually high number of retranslations. By analysing sixteen interviews with Iranian translators and publishers and performing paratextual analysis of four retranslations of George Orwell’s Animal Farm, this paper sheds light on the perceived advantages and disadvantages of retranslation. It does so by drawing on the trust-based approach to the study of translation proposed by Rizzi, Lang, and Pym, and by offering sociological insight into retranslation in contemporary Iran. Four groups of translators are identified: amateur, early career, mid-career, and senior translators. Retranslation for the former two groups is viewed as profitable trade in literary translation market. For the latter two, retranslation is the process of reinforcing trustworthiness at the institutional level that means trust in professionalism of certain Iranian translators and publishers.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.570
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.215
GPT teacher head0.337
Teacher spread0.121 · 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.

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

Citations4
Published2020
Admission routes1
Has abstractyes

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