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Record W2059390109 · doi:10.7202/017980ar

Visual Aspects of Intercultural Technical Communication: A Cognitive Scientific and Semiotic Point of View

2008· article· en· W2059390109 on OpenAlexvenueno aff
Hanna Risku, Richard Pircher

Bibliographic record

VenueMeta Journal des traducteurs · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsSemioticsCognitionTranslation studiesPoint (geometry)Technical communicationVisual communicationComputer scienceAgency (philosophy)LinguisticsCognitive sciencePsychologySociologyMultimediaEngineeringSocial science

Abstract

fetched live from OpenAlex

This article presents a cognitive scientific view of the role of verbal and visual aspects in the translation of technical texts. The semiotic differentiation between symbols and icons is discussed from both the cognitive scientific and the translation studies perspectives. The article refers to the definition of text as a unit of communication (and translation) that includes both verbal and visual aspects and thus emphasises the function of the visual dimension in translation. The theoretical discussion is related to professional practices in the modern translation workplace: through its discussion of the results of a recent empirical field study based on participant observation over an extended period of time in a translation agency, the present research seeks to determine the extent to which the visual dimension can be taken into account in technical translation. In particular, the results point to the consequences of the use of translation technologies (translation memories, translation management systems, localisation software, etc.) in the modern translation workplace. The dominance of the verbal aspect induced by the use of some such technologies can make it increasingly difficult for translators to pay attention to the visual elements in translation. This stresses the importance of the inclusion of courses on the critical and professional use of translation technologies within translation studies programmes.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score0.677

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 studies0.0010.002
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 head0.105
GPT teacher head0.314
Teacher spread0.209 · 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 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

Citations17
Published2008
Admission routes1
Has abstractyes

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