Reading takes it all? – the role of language competence and subject knowledge in legal translation

References

• Alcaraz Varó, E., and B. Hughes. 2014. Legal Translation Explained. London and New York: Routledge.
   Google Scholar
• Alvarez-Vidal, S., A. Oliver, and T. Badia. 2021. “What Do Post-Editors Correct? A Fine-Grained Analysis of SMT and NMT Errors.” Tradumàtica tecnologies de la traducció 19 (19): 131–147. https://doi.org/10.5565/rev/tradumatica.286.
   Google Scholar
• Aranberri, N., G. Labaka, A. de Ilarraza, and K. Sarasola 2014. “Comparison of Post-Editing Productivity Between Professional Translators and Lay Users.” In: Proceedings of the Third Workshop on Post-Editing Technology and Practice, edited by S. O’Brien, M. Simard, and L. Specia, 20–33. Vancouver: Association for Machine Translation in the Americas.
   Google Scholar
• Bangalore, S., B. Behrens, M. Carl, M. Ghankot, A. Heilmann, J. Nitzke, M. Schaeffer, and A. Sturm. 2015. “The Role of Syntactic Variation in Translation and Post-Editing.” Translation Spaces 4 (1): 119–144. https://doi.org/10.1075/ts.4.1.06sch.
   Google Scholar
• Biel, L., and D. Koźbiał. 2020. “How Do Translators Handle (Near-) Synonymous Legal Terms? A Mixed-Genre Parallel Corpus Study into the Variation of EU English-Polish Competition Law Terminology.” Estudios de Traducción 10:69–90. https://doi.org/10.5209/estr.68054.
   Web of Science ®Google Scholar
• Budin, G., Z. Krajcso, and A. Lommel. 2013. “The TransCert Project: Ensuring That Transnational Translator Certification Meets Stakeholder Needs.” Translation & Interpreting: The International Journal of Translation and Interpreting Research 5 (1): 143–155. https://doi.org/10.12807/ti.105201.2013.a08.
   Google Scholar
• Carl, M., B. Dragsted, J. Elming, D. Hardt, and A. L. Jakobsen. 2011. “The Process of Post-Editing: A Pilot Study.” In: Proceedings of the 8th International NLPCS Workshop. Special Theme: Human-Machine Interaction in Translation, edited by B. Sharp, M. Zock, M. Carl, and A. L. Jakobsen, 131–142. Frederiksberg: Samfundslitteratur.
   Google Scholar
• Carl, M., S. Gutermuth, and S. Hansen-Schirra. 2015. “Post-Editing Machine Translation: Efficiency, Strategies and Revision Processes in Professional Translation Settings.” In Psycholinguistic and Cognitive Inquiries into Translation and Interpreting, edited by A. Ferreira and J. Schwieter, 145–174. Amsterdam/Philadelphia: John Benjamins.
   Google Scholar
• Carl, M., and M. Schaeffer. 2017. “Why Translation Is Difficult: A Corpus-Based Study of Non-Literality in Post-Editing and From-Scratch Translation.” HERMES – Journal of Language and Communication in Business 56 (56): 43–57. https://doi.org/10.7146/hjlcb.v0i56.97201.
   Google Scholar
• Čulo, O., and J. Nitzke 2016. “Patterns of Terminological Variation in Post-Editing and of Cognate Use in Machine Translation in Contrast to Human Translation.” In: Proceedings of the 19th Annual Conference of the European Association for Machine Translation Riga, Latvia, 106–114.
   Google Scholar
• Daems, J., S. Vandepitte, R. Hartsuiker, and L. Macken. 2017. “Translation Methods and Experience: A Comparative Analysis of Human Translation and Post-Editing with Students and Professional Translators.” Meta: Journal Des Traducteurs/Meta: Translators’ Journal 62 (2): 245–270. https://doi.org/10.7202/1041023ar.
   Web of Science ®Google Scholar
• Do Carmo, F., and J. Moorkens. 2020. “Differentiating Editing, Post-Editing and Revision.” In Translation Revision and Post-Editing, edited by M. Koponen, B. Mossop, I. Rober, and G. Scocchera, 35–49. London and New York: Routledge.
   Google Scholar
• EMT (European Master’s in Translation). 2022. Updated Version of the EMT Competence Framework. Brussels: European Commission. https://commission.europa.eu/news/updated-version-emt-competence-framework-now-available-2022-10-21_en.
   Google Scholar
• Fiederer, R., and S. O’Brien. 2009. “Quality and Machine Translation: A Realistic Objective.” Journal of Specialised Translation 11 (1): 52–74.
   Google Scholar
• García, I. 2010. “Is Machine Translation Ready Yet?” Target 22 (1): 7–21. https://doi.org/10.1075/target.22.1.02gar.
   Web of Science ®Google Scholar
• Ginovart Cid, C., and C. Colominas Ventura. 2020. “The MT Post-Editing Skill Set: Course Descriptions and Educators’ Thoughts.” In Translation Revision and Post-Editing, edited by M. Koponen, B. Mossop, I. Rober, and G. Scocchera, 226–246. London and New York: Routledge. https://doi.org/10.4324/9781003096962-17.
   Google Scholar
• Guerberof Arenas, A., and J. Moorkens. 2019. “Machine Translation and Post-Editing Training As Part of a master’s Programme.” Jostrans: The Journal of Specialised Translation 31: 217–238.
   Google Scholar
• Hurtado Albir, A., ed. 2017. Researching Translation Competence by PACTE Group. Amsterdam/Philadelphia: John Benjamins.
   Google Scholar
• Jia, Y., M. Carl, and X. Wang. 2019. “How Does the Post-Editing of Neural Machine Translation Compare with From-Scratch Translation? A Product and Process Study.” Journal of Specialised Translation 31: 60–86.
   Web of Science ®Google Scholar
• Killman, J. 2014. “Vocabulary Accuracy of Statistical Machine Translation in the Legal Context”. In: Proceedings of the Third Workshop on Post-Editing Technology and Practice (WPTP-3), The 11th Conference of the Association for Machine Translation in the Americas, 22–26 October 2014, Vancouver, BC, Canada, edited by S. O’Brien, M. Simard, and L. Specia, 85–98. Vancouver: Association for Machine Translation in the Americas.
   Google Scholar
• Killman, J., and M. Rodríguez-Castro. 2022. “Post-Editing Vs. Translating in the Legal Context: Quality and Time Effects from English to Spanish.” Revista de Llengua i Dret 78:56–72. https://doi.org/10.2436/rld.i78.2022.3831.
   Google Scholar
• Kiraly, D. 2005. “Project-Based Learning: A Case for Situated Translation.” Meta: Journal des traducteurs 50 (4): 1098–1111. https://doi.org/10.7202/012063ar.
   Web of Science ®Google Scholar
• Krajcsó, Z. 2018. “Translators’ Competence Profiles Vs. Market Demand.” Babel 64 (5–6): 692–709. https://doi.org/10.1075/babel.00059.kra.
   Google Scholar
• Krings, H. P. 2001. Repairing Texts: Empirical Investigations of Machine Translation Post-Editing Processes, Translated by G. S. Koby. Kent, OH: The Kent State University Press.
   Google Scholar
• Lesznyák, M., and D. Balogh. 2019. “Comparative Analysis of Translations Prepared by Students with and without Legal Qualifications.” Comparative Legilinguistics 37 (1): 85–115. https://doi.org/10.14746/cl.2019.37.3.
   Google Scholar
• Mariana, V., T. Cox, and A. Melby. 2015. “The Multidimensional Quality Metrics (MQM) Framework: A New Framework for Translation Quality Assessment.” The Journal of Specialized Translation 23: 137–161.
   Google Scholar
• Martindale, M. J., and M. Carpuat. 2018. “Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT.” arXiv preprint arXiv:1802.06041. https://arxiv.org/abs/1802.06041.
   Google Scholar
• Mbotake, S. G. 2013. “The Impact of Language Competence on Translation Performance. A Case Study.” African Journal of Social Sciences 4 (2): 51–65.
   Google Scholar
• Neubert, A. 2000. “Competence in Language, in Languages, and in Translation.” In Developing Translation Competence, edited by C. Schäffner and B. Adab, 3–18. Amsterdam: John Benjamins. https://doi.org/10.1075/btl.38.03neu.
   Google Scholar
• Nitzke, J., and S. Hansen-Schirra. 2021. A Short Guide to Post-Editing. Berlin: Language Science Press. https://doi.org/10.2581/zenodo564689.
   Google Scholar
• Nitzke, J., S. Hansen-Schirra, and C. Canfora. 2019. “Risk Management and Post-Editing Competence.” The Journal of Specialized Translation 31: 239–259.
   Web of Science ®Google Scholar
• Noronha Cunha, S. 2023. “MT and Legal Translation: Applications in Training.” In: Proceedings of Machine Translation Summit XIX, 2 Macau SAR, China, 11–23.
   Google Scholar
• Northcott, J., and G. Brown. 2006. “Legal Translator Training: Partnership Between Teachers of English for Legal Purposes and Legal Specialists.” English for Specific Purposes 25 (3): 358–375. https://doi.org/10.1016/j.esp.2005.08.003.
   Web of Science ®Google Scholar
• PACTE. 2003. “Building a Translation Competence Model.” In Triangulating Translation: Perspectives in Process Oriented Research, edited by F. Alves, 43–66. Amsterdam: John Benjamins.
   Google Scholar
• PACTE. 2008. “First Results of a Translation Competence Experiment: ‘Knowledge of Translation’ and ‘Efficacy of Translation Process’.” In Translator and Interpreter Training: Issues, Methods and Debates, edited by J. Kearns, 104–126. London: Continuum.
   Google Scholar
• PACTE Group. 2017a. “PACTE Translation Competence Model: A Holistic, Dynamic Model of Translation Competence.” In Researching Translation Competence by PACTE Group, edited by A. Hurtado Albir, 35–41. Amsterdam/Philadelphia: John Benjamins.
   Google Scholar
• PACTE Group. 2017b. “The Second Stage of PACTE group’s Research. Experimental Research into the Acquisition of Translation Competence.” In Researching Translation Competence by PACTE Group, edited by A. Hurtado Albir, 303–308. Amsterdam/Philadelphia: John Benjamins.
   Google Scholar
• PACTE Research Group. 2014. “First Results of PACTE Group’s Experimental Research on Translation Competence Acquisition: The Acquisition of Declarative Knowledge of Translation.” MonTI: Monografías de Traducción e Interpretación 85–115. https://doi.org/10.6035/MonTI.2014.ne1.2.
   Google Scholar
• Plitt, M., and F. Masselot. 2010. “A Productivity Test of Statistical Machine Translation Post-Editing in a Typical Localisation Context.” The Prague Bulletin of Mathematical Linguistics 93 (1): 7–16. https://doi.org/10.2478/v10108-010-0010-x.
   Google Scholar
• Prieto Ramos, F. 2011. “Developing Legal Translation Competence: An Integrative Process-Oriented Approach.” Comparative Legilinguistics 5:7–21. https://doi.org/10.14746/cl.2011.5.01.
   Google Scholar
• Prieto Ramos, F. 2015. “Quality Assurance in Legal Translation: Evaluating Process, Competence and Product in the Pursuit of Adequacy.” International Journal for the Semiotics of Law – Revue internationale de Sémiotique juridique 28 (1): 11–30. https://doi.org/10.1007/s11196-014-9390-9.
   Google Scholar
• Prieto Ramos, F. 2021. “Translating Legal Terminology and Phraseology: Between Inter-Systemic Incongruity and Multilingual Harmonization.” Perspectives 29 (2): 175–183. https://doi.org/10.1080/0907676X.2021.1849940.
   Google Scholar
• Pym, A. 1992. “Translation Error Analysis and the Interface with Language Teaching.” In The Teaching of Translation, edited by C. Dollerup and A. Loddegaard, 279–288. Amsterdam: John Benjamins. https://doi.org/10.1075/z.56.42pym.
   Google Scholar
• Šarčević, S. 1997. New Approach to Legal Translation. Hague: Kluwer Law International.
   Google Scholar
• Screen, B. 2016. “What Does Translation Memory Do to Translation? The Effect of Translation Memory Output on Specific Aspects of the Translation Process.” International Journal of Translation & Interpreting Research 8 (1): 1–18. https://doi.org/10.12807/ti.108201.2016.a01.
   Web of Science ®Google Scholar
• Sosoni, V., J. O’Shea, and M. Stasimioti. 2022. “Translating Law: A Comparison of Human and Post-Edited Translations from Greek to English.” Revista de Llengua I Dret, Journal of Language and Law 78:92–120. https://doi.org/10.2436/rld.i78.2022.3704.
   Google Scholar
• Svoboda, T., and V. Sosoni. 2023. “Institutional Translator Training in Language and Translation Technologies.” In Institutional Translator Training, edited by T. Svoboda, L. Biel, and V. Sosoni, 73–91. New York: Routledge. https://doi.org/10.4324/9781003225249-6.
   Google Scholar
• Toral, A. 2019. “Post-Editese: An Exacerbated Translationese.” In: Proceedings of Machine Translation Summit XVII: Research Track. 273–281. Dublin: European Association for Machine Translation.
   Google Scholar
• Ureel, J., E. Diels, I. Robert, and I. Schrijver. 2021. “The Development of L2 Sociolinguistic Competence in Translation Trainees: An Accommodation-Based Longitudinal Study into the Acquisition of Sensitivity to Grammatical (In)formality in English.” The Interpreter and Translator Trainer 16 (1): 78–95. https://doi.org/10.1080/1750399X.2021.1900712.
   Web of Science ®Google Scholar
• Vardaro, J., M. Schaeffer, and S. Hansen-Schirra. 2019. “Translation Quality and Error Recognition in Professional Neural Machine Translation Post-Editing.” Informatics 6 (3): 41. https://doi.org/10.3390/informatics6030041.
   Google Scholar
• Vieira, N., M. O’Hagan, and C. O’ Sullivan. 2021. “Understanding the Societal Impacts of Machine Translation: A Critical Review of the Literature on Medical and Legal Use Cases.” information communication & society 24 (11): 1515–1532. https://doi.org/10.1080/1369118X.2020.1776370.
   Web of Science ®Google Scholar
• Way, A. 2018. “Quality Expectations of Machine Translation.” In Translation Quality Assessment: From Principles to Practice, edited by M. Joss, C. Sheila, G. Federico, and D. Stephen, 159–178. Cham: Springer.
   Google Scholar
• Yamada, M. 2019. “The Impact of Google Neural Machine Translation on Post-Editing by Student Translators.” Journal of Specialised Translation 31: 87–106.
   Web of Science ®Google Scholar
• Zaretskaya, A. 2017. “Machine Translation Post-Editing at TransPerfect – the ‘Human’ Side of the Process.” Tradumàtica tecnologies de la traducció 15 (15): 116–123. https://doi.org/10.5565/rev/tradumatica.201.
   Google Scholar