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Record W2074282569 · doi:10.7202/1023808ar

Revisiting the Translator’s Visibility: Does Visibility Bring Rewards?

2014· article· en· W2074282569 on OpenAlexvenueno aff

Bibliographic record

VenueMeta Journal des traducteurs · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
FundersUniversitat Rovira i Virgili
KeywordsVisibilityHabitusPrestigeSocial capitalInterpreterField (mathematics)Empirical researchSociologyCapital (architecture)Qualitative researchContent analysisChinaPublic relationsCultural capitalSocial psychologyPsychologyPolitical scienceLinguisticsSocial scienceComputer scienceHistoryEpistemologyGeographyLaw

Abstract

fetched live from OpenAlex

There has been a huge revival of interest in the role of translators and their visibility. Some Translation Studies scholars have mobilized French sociologist Pierre Bourdieu’s theorical concepts of field , habitus and capital to carry out empirical research studies in an attempt to understand how translators or interpreters perceive their roles and what kind of capital they pursue. This article presents part of the findings from a large empirical study in which quantitative and qualitative approaches are combined in an attempt to carry out a thorough investigation of translators’ visibility, understood as the capacity to communicate directly with clients and/or end-users. The present article reports on the quantitative analysis of the relationship between translator’s visibility and the amount of capital that they say they receive. The analysis is based on 193 Chinese translators in China, Hong Kong, Taiwan and Macao. The findings suggest that visibility is rewarding in terms of social exchanges and learning experience, but not in terms of pay and prestige. In addition, the analysis shows that some social variables including sex, level of education, region that the translator lives in, the translator’s major field of study and the time spent on translation are not related to visibility or capital received. Meanwhile, the appearance of the translator’s name on translations is significantly related to the capital received.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.064
GPT teacher head0.286
Teacher spread0.222 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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