When Correct Isn’t Fluent: Translationese in Turkish-to-English Academic Writing and Its Implications for EAP
Abstract
Turkish scholars, like many non-native English speakers, routinely translate manuscripts written in their first language before submitting them to international journals, a practice that leaves linguistic traces even in grammatically sound texts. This study examines that residue, commonly termed translationese, in the introductions of 40 bilingual articles from Education and Science, an SSCI- and Scopus-indexed Turkish education journal, using a reference-free neural quality-estimation metric (COMET-QE) to score each English introduction against its Turkish source. After excluding five articles for alignment issues, scores across the remaining 35 clustered within a comparatively narrow band (M = 0.68), suggesting source-language interference is pervasive rather than occasional in this corpus. Contrary to expectation, neither how much a translation expanded relative to its source nor its raw length showed a significant relationship with its score. Close analysis of the lowest- and highest-scoring texts instead pointed to specific choices, such as calque, repetitive noun-phrase reference in place of pronouns, and clause structures that preserved Turkish syntax at English's expense, as more reliable markers of quality than any global text property. For English Language Teaching, particularly academic writing instruction for Turkish-speaking researchers, these findings suggest that raising awareness of specific interference patterns may serve learners better than generic fluency advice, and that quality-estimation tools could support self-editing before submission.
Keywords
References
- Acı, M., Vuran Sarı, N., & İnan Acı, Ç. (2025). Morphological and structural complexity analysis of low-resource English-Turkish language pair using neural machine translation models. *PeerJ Computer Science, 11*, e3072. https://doi.org/10.7717/peerj-cs.3072
- Ackermann, K., & Chen, Y.-H. (2013). Developing the Academic Collocation List (ACL) – A corpus-driven and expert-judged approach. *Journal of English for Academic Purposes, 12*(4), 235–247. https://doi.org/10.1016/j.jeap.2013.08.002
- Baker, M. (1993). Corpus linguistics and translation studies: Implications and applications. In M. Baker, G. Francis, & E. Tognini-Bonelli (Eds.), *Text and technology: In honour of John Sinclair* (pp. 233–252). John Benjamins. https://doi.org/10.1075/z.64
- Baroni, M., & Bernardini, S. (2006). A new approach to the study of translationese: Machine-learning the difference between original and translated text. *Literary and Linguistic Computing, 21*(3), 259–274. https://doi.org/10.1093/llc/fqi039
- Casal, J. E., & Lee, J. J. (2019). Syntactic complexity and writing quality in assessed first-year L2 writing. *Journal of Second Language Writing, 44*, 51–62. https://doi.org/10.1016/j.jslw.2019.03.005
- Cavalin, P., Domingues, P. H., & Pinhanez, C. (2025). Sentence-level aggregation of lexical metrics correlates stronger with human judgements than corpus-level aggregation. *Proceedings of the AAAI Conference on Artificial Intelligence, 39*(22), 23532–23540. https://doi.org/10.1609/aaai.v39i22.34522
- Chesterman, A. (2004). Hypotheses about translation universals. In G. Hansen, K. Malmkjær, & D. Gile (Eds.), *Claims, changes and challenges in translation studies: Selected contributions from the EST Congress, Copenhagen 2001* (pp. 1–13). John Benjamins.
- Dogru, G., & Moorkens, J. (2024). Data augmentation with translation memories for desktop machine translation fine-tuning in 3 language pairs. *The Journal of Specialised Translation*, (41), 149–178. https://doi.org/10.26034/cm.jostrans.2024.4716
Details
Primary Language
English
Subjects
Translation and Interpretation Studies, English As A Second Language, Translation Studies
Journal Section
Research Article
Authors
Mustafa Dolmacı
*
0000-0002-2503-6072
Türkiye
Publication Date
September 10, 2026
Submission Date
July 28, 2026
Acceptance Date
August 31, 2026
Published in Issue
Year 2026 Volume: 9 Number: 1