Machine translation literacy in the legal translation context: a SWOT analysis perspective

References

• Alcaraz Varó, E. 2009. “Isomorphism and Anisomorphism in the Translation of Legal Texts.” In Translation Issues in Language and Law, edited by F. Olsen, A. Lorz, and D. Stein, 182–192. New York: Palgrave Macmillan.
   Google Scholar
• Alcaraz Varó, E., and B. Hughes. 2002. Legal Translation Explained. Manchester: St. Jerome Publishing.
   Google Scholar
• Alonso Jiménez, E., and E. C. Encinas. 2015. “Developing a Blueprint for a Technology-Mediated Approach to Translation Studies.” Meta 60 (1): 135–157. https://doi.org/10.7202/1032403ar.
   Web of Science ®Google Scholar
• Arnejšek, M., and A. Unk. 2020. “Multidimensional Assessment of the eTranslation Output for English-Slovene.” In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 3–5 November 2020, Lisbon, Portugal, edited by A. Martins, H. Moniz, S. Fumega, B. Martins, F. Batista, L. Coheur, and C. Parra, 383–392. https://aclanthology.org/2020.eamt-1.pdf.
   Google Scholar
• Arnold, D. 2003. “Why Translation Is Difficult for Computers.” In Computers and Translation: A Translator’s Guide, edited by H. Somers, 119–142. Amsterdam: John Benjamins.
   Google Scholar
• Bago, P., S. Castilho, E. Celeste, J. Dunne, F. Gaspari, G. Rúnar, K. Níels. 2022. “Sharing High-Quality Language Resources in the Legal Domain to Develop Neural Machine Translation for Under-Resourced European Languages.” Revista de Llengua I Dret, Journal of Language and Law 78:9–34. https://doi.org/10.2436/rld.i78.2022.3741.
   Google Scholar
• Bahdanau, D., K. H. Cho, and Y. Bengio. 2015. “Neural Machine Translation by Jointly Learning to Align and Translate.” In Proceedings of the International Conference on Learning Representations, 7–8 May 2015, San Diego, CA, USA. https://arxiv.org/abs/1409.0473.
   Google Scholar
• Bar-Hillel, Y. 1960. “The Present Status of Automatic Translation of Languages.” Advances in Computers 1:91–163.
   Google Scholar
• Bentivogli, L., A. Bisazza, M. Cettolo, and M. Federico. 2016. “Neural versus Phrase-Based Machine Translation Quality: A Case Study.” In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 1–5 November 2016, Austin, Texas, USA, 257–267. Red Hook, New York: Curran Associates.
   Google Scholar
• Biau, G., R. José, and P. Anthony. 2006. “Technology and Translation (A Pedagogical Overview).” In Translation Technology and Its Teaching, edited by A. Pym, A. Perekrestenko, and B. Starink, 5–19. Tarragona: Universitat Rovira i Virgili.
   Google Scholar
• Biel, Ł. 2017. “Researching Legal Translation: A Multi-Perspective and Mixed-Method Framework for Legal Translation.” Revista de Llengua I Dret, Journal of Language and Law 68:76–188. https://doi.org/10.2436/rld.i68.2017.2967.
   Google Scholar
• Bojar, O., R. Chatterjee, C. Federmann, Y. Graham, B. Haddow, M. Huck, A. Jimeno Yepes, et al. 2016. “Findings of the 2016 Conference on Machine Translation.” In Proceedings of the First Conference on Machine Translation of the Association for Computational Linguistics, Volume 2: Shared Task Papers, 11–12 August 2016, Berlin, Germany, 131–198, edited by O. Bojar, C. Buck, R. Chatterjee, C. Federmann, L. Guillou, B. Haddow, and M. Huck, https://aclanthology.org/volumes/W16-23/
   Google Scholar
• Borja Albi, A. 2005. “¿Es posible traducir realidades jurídicas? Restricciones y prioridades en la traducción de documentos de sucesiones británicos al español.” In La traducción y la interpretación en las relaciones jurídicas internacionales, edited by E. M. Nebot and A. B. Albi, 65–89. Castelló de la Plana: Publicacions de la Universitat Jaume I.
   Google Scholar
• Bourdaillet, J., S. Huet, P. Langlais, and G. Lapalme. 2010. “TransSearch: From a Bilingual Concordancer to a Translation Finder.” Machine Translation 24 (3–4): 241–271. https://doi.org/10.1007/s10590-011-9089-6.
   Google Scholar
• Briva-Iglesias, V. 2021. “Traducción humana vs. traducción automática: análisis contrastivo e implicaciones para la aplicación de la traducción automática en traducción jurídica.” Mutatis Mutandis 14 (2): 571–600. https://doi.org/10.17533/udea.mut.v14n2a14.
   Google Scholar
• Cadwell, P., S. Castilho, S. O’Brien, and L. Michell. 2016. “Human Factors in Machine Translation and Post-Editing Among Institutional Translators.” Translation Spaces 5 (2): 222–243. https://doi.org/10.1075/ts.5.2.04cad.
   Web of Science ®Google Scholar
• Cadwell, P., S. O’Brien, and C. S. C. Teixeira. 2018. “Resistance and Accommodation: Factors for the (Non-) Adoption of Machine Translation Among Professional Translators.” Perspectives 26 (3): 301–321. https://doi.org/10.1080/0907676X.2017.1337210.
   Web of Science ®Google Scholar
• Cao, D. 2007. Translating Law. Clevedon: Multilingual Matters.
   Google Scholar
• Castilho, S., J. Moorkens, F. Gaspari, I. Calixto, J. Tinsley, and A. Way. 2017. “Is Neural Machine Translation the New State of the Art?” The Prague Bulletin of Mathematical Linguistics 108 (1): 109–120. https://doi.org/10.1515/pralin-2017-0013.
   Google Scholar
• Castilho, S., J. Moorkens, F. Gaspari, R. Sennrich, V. Sosoni, P. Georgakopoulou, P. Lohar, et al. 2017. “A Comparative Quality Evaluation of PBSMT and NMT Using Professional Translators.” In Proceedings of MT Summit XVI. Volume 1: Research Track, 18–22 September 2017, Nagoya, Japan, 116–131. https://doras.dcu.ie/23083/1/A%20Comparative%20Quality%20Evaluation%20of%20PBSMT%20and.pdf.
   Google Scholar
• Chromá, M. 2011. “Synonymy and Polysemy in Legal Terminology and Their Application to Bilingual and Bijural Translation.” Research in Language 9 (1): 31–50. https://doi.org/10.2478/v10015-011-0004-2.
   Google Scholar
• Chromá, M. 2014. “Making Sense in Legal Translation.” Semiotica 2014 (201): 121–144. https://doi.org/10.1515/sem-2014-0018.
   Google Scholar
• Desmet, L. 2021. “An Exploratory Study of Professional Post-Edits by English-Dutch DGT Translators.” MA thesis, Ghent University.
   Google Scholar
• Dik, H. 2020. “CTRL+V for Verdict: An Analysis of Dutch to English Legal Machine Translation.” MA thesis, Leiden University.
   Google Scholar
• Duro Moreno, M. 2012. “El modelo de los entornos de la traducción: aplicaciones didácticas a la traducción jurídica.” In À propos de l’enseignement de la traduction et l’interprétation en Europe/Sobre la enseñanza de la traducción y la interpretación en Europa, edited by E. O. Arjonilla, C. Balliu, E. A. Navío, and A. B. M. López, 279–288. Granada: Comares.
   Google Scholar
• Farzindar, A., and G. Lapalme. 2009. “Machine Translation of Legal Information and Its Evaluation.” In Advances in Artificial Intelligence, edited by Y. Gao and N. Japkowicz, 64–73. Berlin: Springer.
   Google Scholar
• Forcada, M. L. 2010. “Machine Translation Today.” In Handbook of Translation Studies: Volume 1, edited by Y. Gambier and L. van Doorslaer, 215–223. Amsterdam: John Benjamins.
   Google Scholar
• Forcada, M. L. 2017. “Making Sense of Neural Machine Translation.” Translation Spaces 6 (2): 291–309. https://doi.org/10.1075/ts.6.2.06for.
   Web of Science ®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
• García, I. 2011. “Translating by Post-Editing: Is it the Way Forward?” Machine Translation 25 (3): 217–237. https://doi.org/10.1007/s10590-011-9115-8.
   Google Scholar
• Glanert, S. 2014. “Law-In-Translation: An Assemblage in Motion.” The Translator 20 (3): 255–272. https://doi.org/10.1080/13556509.2014.945270.
   Web of Science ®Google Scholar
• González Pastor, D., and C. Rico. 2021. “POSEDITrad: la traducción automática y la posedición para la formación de traductores e intérpretes.” Revista Digital de Investigación En Docencia Universitaria 15 (1): e1213. https://doi.org/10.19083/10.19083/ridu.2021.1213.
   Google Scholar
• Gotti, F., A. Farzindar, G. Lapalme, and E. Macklovitch. 2008. “Automatic Translation of Court Judgments.” In Proceedings of The Eighth Conference of the Association for Machine Translation in the Americas: Government and Commercial Uses of MT, 21–25 October 2008, Waikiki, Hawaii, USA, 370–379. https://aclanthology.org/volumes/2008.amta-govandcom
   Google Scholar
• Harvey, M. 2002. “What’s so Special About Legal Translation?” Meta 47 (2): 177–185. https://doi.org/10.7202/008007ar.
   Web of Science ®Google Scholar
• Heiss, C., and M. Soffritti. 2018. “DeepL Traduttore e didattica della traduzione dall’italiano in tedesco.” inTralinea. http://www.intralinea.org/specials/tail.
   Google Scholar
• Hutchins, J. 2010. “Machine Translation: A Concise History.” Journal of Translation Studies 13 (1–2): 29–70.
   Google Scholar
• Junczys-Dowmunt, M., D. Tomasz, and H. Hieu 2016. “Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions.” In Proceedings of the 13th International Conference on Spoken Language Translation, 8-9 December 2016, Seattle, WA, USA, edited by M. Cettolo, J. Niehues, S. Stüker, L. Bentivogli, R. Cattoni, and M. Federico. https://aclanthology.org/volumes/2016.iwslt-1/
   Google Scholar
• Kenny, D., and S. Doherty. 2014. “Statistical Machine Translation in the Translation Curriculum: Overcoming Obstacles and Empowering Translators.” The Interpreter and Translator Trainer 8 (2): 276–294. https://doi.org/10.1080/1750399X.2014.936112.
   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: AMTA.
   Google Scholar
• Killman, J. 2015. “Context As Achilles’ Heel of Translation Technologies: Major Implications for End-Users.” Translation & Interpreting Studies 10 (2): 203–222. https://doi.org/10.1075/tis.10.2.03kil.
   Web of Science ®Google Scholar
• Killman, J. 2018a. “A Context-Based Approach to Introducing Translation Memory in Translator Training.” In Translation, Globalization and Translocation, edited by C. Godev, 137–159. London: Palgrave Macmillan.
   Google Scholar
• Killman, J. 2018b. “Translating the Same Text Twice: An English-Spanish Comparative Product Study of Post-Edited Translations Vs. Human Translations.” Journal of Internationalization and Localization 5 (2): 114–141. https://doi.org/10.1075/jial.18003.kil.
   Google Scholar
• Killman, J. 2023a. “Machine Translation and Legal Terminology: Data-Driven Approaches to Contextual Accuracy.” In Handbook of Legal Terminology, edited by Ł. Biel and H. J. Kockaert, 485–510. Amsterdam: John Benjamins.
   Google Scholar
• Killman, J. 2023b. “Rendering Morphosyntactic Features of Legal Spanish Judgments Using Neural and Statistical Machine Translation.” In New Advances in Legal Translation and Interpreting, edited by J. Zhao and D. Li, 221–242. Singapore: Springer Nature.
   Google Scholar
• Killman, J. 2024. “Machine Translation in the Legal Context: A Spanish-To-English Comparative Product Study of Statistical Vs. Neural MT Output.” In Translation, Interpreting and Technological Change: Innovations in Research, Practice and Training, edited by M. Winters, S. Deane-Cox, and U. Böser, 136–156. London: Bloomsbury.
   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, Journal of Language and Law 78:56–72. https://doi.org/10.2436/rld.i78.2022.3831.
   Google Scholar
• Kit, C., and T. M. Wong. 2008. “Comparative Evaluation of Online Machine Translation Systems with Legal Texts.” Law Library Journal 100 (2): 299–321.
   Web of Science ®Google Scholar
• Kjær, A. L. 1990. “Context-Conditioned Word Combinations in Legal Language.” Journal of the International Institute for Terminology Research 1 (1–2): 21–32.
   Google Scholar
• Koehn, P. 2005. “Europarl: A Parallel Corpus for Statistical Machine Translation.” In Proceedings of Machine Translation Summit X, 13–15 September 2005, Phuket, Thailand, 79–86. https://aclanthology.org/2005.mtsummit-papers.11/
   Google Scholar
• Koehn, P. 2020. Neural Machine Translation. Cambridge: Cambridge University Press.
   Google Scholar
• Koehn, P., and R. Knowles. 2017. “Six Challenges for Neural Machine Translation.” In Proceedings of the First Workshop on Neural Machine Translation of the Association for Computational Linguistics, 4 August 2017, Vancouver, BC, Canada, edited by T. Luong, A. Birch, G. Neubig, and A. Finch, 28–39. Stroudsburg, Pennsylvania, USA: Association for Computational Linguistics.
   Google Scholar
• Koehn, P., F. J. Och, and D. Marcu. 2003. “Statistical Phrase-Based Translation.” In Proceedings of the 2003 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, 27 May–1 June, Edmonton, Canada, 127–133. https://aclanthology.org/volumes/N03-1/
   Google Scholar
• Lesznyák, Á. 2019. “Hungarian Translators’ Perceptions of Neural Machine Translation in the European Commission.” In Proceedings of MT Summit XVIII: Translator, Project and User Tracks, 19–23 August 2019, Dublin, edited by M. Forcada, A. Way, J. Tinsley, D. Shterionov, C. Rico, and F. Gaspari, 16–22. https://aclanthology.org/volumes/W19-67/
   Google Scholar
• Lewis, T. 1997. “When Not to Use MT and Other Translation Tools.” In EAMT Workshop: Language Technology in your Organization?, 21–22 May 1997, Copenhagen, Denmark, edited by J. Hutchins, 34–41. https://aclanthology.org/1997.eamt-1.
   Google Scholar
• Llopis, O., and M. Ángeles. 2007. “The Untranslatability of Law? Lexical Differences in Spanish and American Contract Law.” European Journal of English Studies 11 (1): 17–28. https://doi.org/10.1080/13825570601183179.
   Google Scholar
• Lommel, A. R., and D. A. DePalma. 2016. Post-Editing Goes Mainstream: How LSPs Use MT to Meet Client Demands. Cambridge, MA: Common Sense Advisory.
   Google Scholar
• Macken, L., D. Prou, and A. Tezcan. 2020. “Quantifying the Effect of Machine Translation in a High-Quality Human Translation Production Process.” Informatics 7 (2): 12. https://doi.org/10.3390/informatics7020012.
   Google Scholar
• Matulewska, A. 2013. Legilinguistic Translatology: A Parametric Approach to Legal Translation. Bern: Peter Lang.
   Google Scholar
• Melby, A., and C. Foster. 2010. “Context in Translation: Definition, Access and Teamwork.” Translation & Interpreting 2 (2): 1–15.
   Google Scholar
• Mellinger, C. D. 2017. “Translators and Machine Translation: Knowledge and Skills Gaps in Translator Pedagogy.” The Interpreter and Translator Trainer 11 (4): 280–293. https://doi.org/10.1080/1750399X.2017.1359760.
   Web of Science ®Google Scholar
• Moorkens, J. 2018. “What to Expect from Neural Machine Translation: A Practical In-Class Translation Evaluation Exercise.” The Interpreter and Translator Trainer 12 (4): 375–387. https://doi.org/10.1080/1750399X.2018.1501639.
   Web of Science ®Google Scholar
• O’Brien, S., and M. Ehrensberger-Dow. 2020. ‘MT Literacy—A cognitive view.’ Translation, Cognition & Behavior 3 (2): 145–164. https://doi.org/10.1075/tcb.00038.obr.
   Google Scholar
• Papineni, K., S. Roukos, T. Ward, and W.-J. Zhu. 2002. “BLEU: A Method for Automatic Evaluation of Machine Translation.” In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, July, Philadelphia, 311–318. https://aclanthology.org/P02-1040.pdf
   Google Scholar
• Plaza Lara, C. 2019. “Análisis DAFO sobre la inclusión de la traducción automática y la posedición en los másteres de la red EMT.” Journal of Specialised Translation 31:260–280.
   Google Scholar
• Prieto Ramos, F. 2011. “Developing Legal Translation Competence: An Integrative Process-Oriented Approach.” Comparative Legilinguistics 5:7–22. https://doi.org/10.14746/cl.2011.5.01.
   Google Scholar
• Prieto Ramos, F. 2014. “International and Supranational Law in Translation: From Multilingual Lawmaking to Adjudication.” The Translator 20 (3): 313–331. https://doi.org/10.1080/13556509.2014.904080.
   Web of Science ®Google Scholar
• Prieto Ramos, F. 2016. “Parameters for Problem-Solving in Legal Translation: Implications for Legal Lexicography and Institutional Terminology Management.” In The Ashgate Handbook of Legal Translation, edited by K. K. S. Le Cheng and A. Wagner, 121–134. London: Routledge.
   Google Scholar
• Prieto Ramos, F., and D. Guzmán. 2021. “Examining Institutional Translation Through a Legal Lens: A Comparative Analysis of Multilingual Text Production at International Organizations.” Target 33 (2): 254–281. https://doi.org/10.1075/target.21003.pri.
   Web of Science ®Google Scholar
• Rico, C., and D. González Pastor. 2022. “The Role of Machine Translation in Translation Education: A Thematic Analysis of Translator Educators’ Beliefs.” Translation & Interpreting 14 (1): 177–197. https://doi.org/10.12807/ti.114201.2022.a010.
   Web of Science ®Google Scholar
• Roiss, S. 2021. “Y las máquinas rompieron a traducir… Consideraciones didácticas en relación con la traducción automática de referencias culturales en el ámbito jurídico.” Trans: Revista de Traductología 25 (25): 491–505. https://doi.org/10.24310/TRANS.2021.v1i25.11978.
   Google Scholar
• Rossi, C., and J.-P. Chevrot. 2019. “Uses and Perceptions of Machine Translation at the European Commission.” Journal of Specialised Translation 31:177–200.
   Google Scholar
• Şahin, M., and N. Dungan. 2014. “Translation Testing and Evaluation: A Study on Methods and Needs.” Translation & Interpreting 6 (2): 67–90.
   Google Scholar
• Sánchez Ramos, Mª del Mar. 2022. “La integración de la traducción automática y la posedición en la traducción jurídica: un análisis DAFO para su implantación en la formación de traducción e interpretación en los servicios públicos.” Revista de Llengua I Dret, Journal of Language and Law 78:121–137. https://doi.org/10.2436/rld.i78.2022.3687.
   Google Scholar
• Šarčević, S. 1997. New Approach to Legal Translation. The Hague: Kluwer Law International.
   Google Scholar
• Simonnæs, I. 2016. “Legal Language: Pragmatic Approaches to Its Interconnectivity with Legal Interpretation and Legal Translation.” Meta 61 (2): 421–438. https://doi.org/10.7202/1037766ar.
   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
• Stasimioti, M., S. Vilelmini, M. Despoina, and K. Katia 2020. “Machine Translation Quality: A Comparative Evaluation of SMT, NMT and Tailored-NMT Outputs.” In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 3–5 November 2020, Lisbon, Portugal, edited by A. Martins, H. Moniz, S. Fumega, B. Martins, F. Batista, L. Coheur, and C. Parra, et al., 441–450. https://aclanthology.org/2020.eamt-1.pdf
   Google Scholar
• Stefaniak, K. 2020. “Evaluating the Usefulness of Neural Machine Translation for the Polish Translators in the European Commission.” In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 3–5 November 2020, Lisbon, Portugal, edited by A. Martins, H. Moniz, S. Fumega, B. Martins, F. Batista, L. Coheur, and C. Parra, et al., 263–269. https://aclanthology.org/2020.eamt-1.pdf
   Google Scholar
• Sutskever, I., O. Vinyals, and Q. V. Le. 2014. “Sequence to Sequence Learning with Neural Networks.” In Advances in Neural Information Processing Systems, edited by Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger, 3104–3112. Montréal: NIPS.
   Google Scholar
• Toral, A., and V. M. Sánchez-Cartagena. 2017. “A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions.” In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, 3–7 April 2017, Valencia, Spain, edited by M. Lapata, P. Blunsom, and A. Koller, 1063–1073. Stroudsburg, Pennsylvania, USA: Association for Computational Linguistics.
   Google Scholar
• Vanallemeersch, T., and H. J. Kockaert. 2010. “Automatic Detection of Inconsistent Phraseology Translation.” Southern African Linguistics and Applied Language Studies 28 (3): 283–290. https://doi.org/10.2989/16073614.2010.545030.
   Web of Science ®Google Scholar
• Van Brussel, L., A. Tezcan, and L. Macken. 2018. “A Fine-Grained Error Analysis of NMT, SMT and RBMT Output for English-To-Dutch.” In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC), 7–12 May 2018, Miyazaki, Japan, edited by N. Calzolari, K. Choukri, C. Cieri, T. Declerck, K. Hasida, H. Isahara, and B. Maegaard, et al., 3799–3804. Paris: European Language Resources Association (ELRA).
   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
• Vaswani, A., N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin. 2017. “Attention Is All You Need.” In Advances in Neural Information Processing Systems, 31st Annual Conference on Neural Information Processing Systems, 4–9 December 2017, Long Beach, CA, USA, Volume 1, edited by U. von Luxburg, S. Bengio, R. Fergus, R. Garnett, I. Guyon, H. Wallach, and S. V. N. Vishwanathan, 5998–6008. Red Hook, NY: Curran Associates.
   Google Scholar
• Vigier-Moreno, F. J., and L. Pérez-Macías. 2022. “Assessing Neural Machine Translation of Court Documents: A Case Study on the Translation of a Spanish Remand Order into English.” Revista de Llengua I Dret, Journal of Language and Law 78:73–91. https://.doi.org/10.2436/rld.i78.2022.3691.
   Google Scholar
• Way, C. 2016. “The Challenges and Opportunities of Legal Translation and Translator Training in the 21st Century.” International Journal of Communication 10:1009–1029.
   Web of Science ®Google Scholar
• Wiesmann, E. 2019. “Machine Translation in the Field of Law: A Study of the Translation of Italian Legal Texts into German.” Comparative Legilinguistics 37 (1): 117–153. https://doi.org/10.14746/cl.2019.37.4.
   Google Scholar
• Yates, S. 2006. “Scaling the Tower of Babel Fish: An Analysis of the Machine Translation of Legal Information.” Law Library Journal 98 (3): 481–500.
   Web of Science ®Google Scholar