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Theme markedness in the translation of student translators

Bibliographic Data

ID21240720
AuthorsRudy Sofyan (0000-0001-6293-9759, Universitas Sumatera Utara, corresponding author)
Year2018
Volume8
Issue1
Publication date2018-05-31
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIndonesian Journal of Applied Linguistics (JOURNAL)
Journal identifiersISSN: 2301-9468 • E-ISSN: 2502-6747
PublisherUniversitas Pendidikan Indonesia (UPI) (PUBLISHER)
DOI10.17509/ijal.v8i1.11463
OpenAlexW2808051947
LanguageEN
Citations received2
References cited9

A good translation product should be able to reflect the typical characteristics of the target language in terms of its function and structure. One of the structure features that can show that the target text (TT) is free from the influence of the structure of the source language (SL) is its theme structure. As there are both marked and unmarked themes, this would be considered as one of the options to characterize the TT structure. This is a research-based article aimed at finding out the extent of theme markedness in the student translators’ TTs. This research used content analysis design, taking 15 student translators as the participants. They were asked to translate two news item texts from English as the source text (ST) into Bahasa Indonesia as the TT. The data were collected using Translog. Based on the data analysis, it was found that: (i) simple unmarked theme (SUT) was the theme most frequently used in both the ST and the TTs; (ii) Indonesian news item texts were characterized by the frequent use of marked themes. This finding indicates that Indonesian news item text puts more emphasis on how the events presented in the text can be easily caught by the readers as SUT is characterized through the use of short clauses with low lexical density. This study concludes that English and Indonesian news item texts share a small number of similarities as most of their clauses are composed of simple marked themes (SMT) but the similarities are outweighed by a large number of differences

Indonesian · Linguistics · Markedness · Source text · World Wide Web · Computer Science · Natural Language Processing Techniques · Philosophy · Psychology · Second Language Acquisition and Learning · Translation Studies and Practices

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Unique citing works2
Citations per year0,5
Citation span2022 - 2024 (3)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 1

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