Abstract While research on translation pedagogy tends to focus on identifying student competences and effective learning modes, it only occasionally addresses the teachers expected to future-proof their students for viable professional careers in a volatile language industry. The present paper reports on a TER survey of translation teachers designed to explore current profiles and positions specifically in the form of (self-)identities, role perceptions and development needs in a rapidly evolving professional environment. Drawing on the responses of over 160 participants from 31 countries, the paper first considers the survey in the broader context of previous studies and then discusses key findings on the respondents' backgrounds, beliefs, identities and perceptions of the skills needed to meet present and future pedagogical challenges. Despite some evidence of entrenchment, the results indicate evolving positions and profiles as teachers see the need to adapt to new professional and technological realities.
Abstract This article examines the Istanbul Gender Museum, with a focus on its first exhibition of 2021, Time to Speak , highlighting its use of multilingualism, translation, and inclusivity. It argues that the museum becomes an institution of active memory by engaging in multiple translation practices: the cultural translation of local and transnational feminist movements and women+ experiences through slogans featured in Time to Speak ; the interlingual translation of these slogans into local languages; the translation of the museum content into English; and the intersemiotic translation of slogans into artwork. The article particularly explores the first two translation practices, contending that the cultural translation of transnational experiences fosters feminist alliances across borders and reshapes movements and demands within new contexts. Additionally, by adopting inclusivity in the form of linguistic and ethnic diversity, through the use of various ethnic languages spoken in Türkiye alongside the artworks, the museum actively reminds its predominantly monolingual citizens of the country's multilingual and multi-ethnic fabric. The article further suggests that museums, especially as they become more global, digital, and interactive, are no longer fixed “memory spaces”, but dynamic sites of “traveling memories”, accommodating multiple remembering practices rather than a singular (national) narrative.
Abstract This paper presents a case study on the Sait Faik Abasıyanık Museum, an author house museum located in Burgazada, Istanbul. It draws on André Lefevere's discussions on “rewritings” and “refractions,” and emphasizes the determining role of agents to argue that literary museums in general and author house museums in particular, can be seen as spaces of translation in the broader sense of the concept, where the lived experience of authors and their literary production are remediated in refractions allowing the creation of new connections and interpretations going beyond the cult of the author and recontextualizing the author and their work within today's concerns. Methodologically, the research combines an on-site exploration of the museum with a comprehensive semi-structured interview with the curator. In addition to exploring the interplay of ideology, poetics and patronage, the paper reflects on the position of the curator as translator together with the limits of curatorial power. The case study shows that the museum opens a new space of translation and refraction, inviting its visitors to engage anew with the author's work and revise their pre-existing knowledge and potential preconceptions.
Abstract One of the First World War fronts, the Isonzo/Soča Front, was located roughly along today's border between Italy and Slovenia. The memory of this heritage is preserved in several museums both in Italy and Slovenia, but the narrative expressed in them can vary considerably and it can influence the way in which the events represented in the museum are experienced by visitors through the translations. In this paper, two museums will be compared, the Museum of the Great War in Cividale in Italy and the Kobarid Museum in Slovenia, which are located in adjacent areas. The aim of the article is to show how different viewpoints on the war and its resolution are reflected in the narratives of the museums, the choice of languages in which the exhibition texts are translated and in the translations themselves. The data collected for each museum (photographs of museum materials, web pages) were analysed qualitatively and compared to elicit common features and differences. Two different viewpoints were explored: 1) the museum as an instance of intersemiotic translation of experiences into images and text, which can help bring forward or marginalize different actors; 2) the museum as a possible means of cultural mediation and reconciliation.
Abstract Political translation in the Chinese context has predominantly focused on discourse produced at the central government level, with comparatively little attention paid to another key institution, the Ministry of Foreign Affairs (MFA). This preliminary study addresses the gap by examining the MFA's regular press conference translations during the former US House Speaker Nancy Pelosi's visit to Taiwan in August 2022, a highly contentious visit that triggered strong protests from Beijing. Using audience design theory and corpus-assisted critical discourse analysis (CDA) as its theoretical framework, this study critically compares the textual features of Chinese and English transcriptions and examines their discursive effects. The study finds that two different images are projected: a tough, aggressive image of China to domestic audiences, and a more tempered and conciliatory one to international audiences. By focusing on the discursive effects of both language versions, this study argues that political translation at the MFA functions as a tool of audience segmentation and border-making, enabled by China's Internet censorship apparatus.
This article focuses on three Catalan linguistic items or structures that were previously used in the verification of the gravitational pull hypothesis: the modal marker caldre, the imperfective-perfective aspect distinction, and a number of light verb constructions with the verb fer conveying emotional states. Since translational effects had been found to occur in connection with them for the English-Catalan language pair, they are taken to be good candidates to test the machine translationese hypothesis, according to which patterns of over- or underrepresentation in human translations (when compared to non-translations in the target language) tend to be exacerbated in machine translation. Two of the three hypotheses put forward in the article are borne out by the data. The study draws on four components of the COVALT corpus. It also throws light on other aspects of the items under scrutiny, such as source text trigger distribution. The findings are relevant in that they highlight concrete (as opposed to abstract) ways in which machine translation departs from idiomatic usage as reflected by distributional frequencies. This tends to happen in human translation too, but machine translation carries the tendency further.
Political translation in the Chinese context has predominantly focused on discourse produced at the central government level, with comparatively little attention paid to another key institution, the Ministry of Foreign Affairs (MFA). This preliminary study addresses the gap by examining the MFA's regular press conference translations during the former US House Speaker Nancy Pelosi's visit to Taiwan in August 2022, a highly contentious visit that triggered strong protests from Beijing. Using audience design theory and corpus-assisted critical discourse analysis (CDA) as its theoretical framework, this study critically compares the textual features of Chinese and English transcriptions and examines their discursive effects. The study finds that two different images are projected: a tough, aggressive image of China to domestic audiences, and a more tempered and conciliatory one to international audiences. By focusing on the discursive effects of both language versions, this study argues that political translation at the MFA functions as a tool of audience segmentation and border-making, enabled by China's Internet censorship apparatus.
This paper examines the role of translator's social networks in literary translation through a case study of Nicky Harman's translation of Jia Pingwa's novel Gaoxing(sic) (literally meaning "Happy"). Jia is one of the most prominent contemporary Chinese writers, and his novel Gaoxing depicts the lives of migrant workers in Xi'an with extensive use of Shaanxi dialect and culture-specific terms. From a sociological approach of translator studies, this paper examines how Harman, a renowned British translator of contemporary Chinese literature, utilized her networks with the author, the editor, and a professional reader during the process of translation. Through detailed analysis of first-hand research materials, including interviews and correspondence, this paper demonstrates the importance of social networks in the process of literary translation, which is not simply a lone translator working with a literary text.
Translated language often carries subtle linguistic markers that set it apart from text originally written in the target language. This study investigates the potential of powerful AI language models to automatically identify these differences, specifically focusing on distinguishing translated texts from original texts. More specifically, this study utilized transformer-based large language models to differentiate translational English and original English. FLOB (Freiburg-LOB Corpus of British English) was selected as the original English corpus, and COCE (Corpus of Chinese-English) was selected as the translational English corpus. Two models were tested: Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT Pretraining Approach (RoBERTa). The factors affecting classification results are investigated through SHAP analysis and analysis of text types that have significantly different error rates. Results show that both models achieved excellent performance, with F1-scores of .864 for BERT and .998 for RoBERTa. The text types miscellaneous, general fiction, skills trade, and hobbies, and humor exhibit significantly higher error rates. Reportage, review, and science exhibit significantly lower error rates. Through SHAP analysis, we find that higher error rates may be attributed to simpler sentences in these three text types and the shared characteristics of translational texts, such as the tendencies for simplification and explicitation. Conversely, lower error rates were associated with text types that did not share these characteristics. In summary, transformer-based large language models show great potential for the automatic classification and analysis of translational sentences.
This study compares normalisation effect in Chinese-to-English translations produced by DeepL, ChatGPT and human translators, and examines its implications for the (in)visibility of human translators in human-machine collaboration. Moving beyond a monolingual comparable corpus design, the study integrates source-language features and applies principal component analysis, random forest modelling and t-SNE visualisation to better capture the impact of translation on linguistic outcomes. The results showed that DeepL outputs exhibited the strongest normalisation tendencies, while ChatGPT-generated translations demonstrated greater likelihood of deviating from target-language conventions. DeepL translation displayed a higher degree of mechanicalness with less autonomy in handling the typological differences between Chinese and English. While ChatGPT translation demonstrated an advantage in cohesion, its tendency to overuse certain linguistic features might create unnaturally elevated tone. These findings highlight the double-edged nature of AI-driven translation technologies: while their consistency and adaptability may support post-editing workflows, their potential influence on how users perceive translation and the role of translators warrants critical attention. We argue that ethical frameworks should not only promote fair recognition of human input but also convey the limitations of translation technology to the end-users, ensuring human intelligence remains central in an increasingly automated translation landscape.
This study examines how national and cultural stereotypes, as depicted in audiovisual media, shape the identities of both the EU and the UK. Using excerpts from the multilingual TV series Parlement (2020), the research focuses on post-Brexit portrayals of stereotypes on screen. Over a period of four years, we surveyed 158 young Europeans to gauge their responses to cultural, historical, and political stereotypes presented in the series. The findings reveal changing attitudes toward EU identity amid ongoing socio-political fragmentation, highlighting the complex interaction between media representation and audience interpretation. Our research illuminates the challenges of fostering cross-cultural cohesion, providing insights into how stereotypes are negotiated in multilingual contexts and underscoring the influential role of audiovisual media in shaping collective identities.
Retranslation creates new versions of previously translated texts, documenting shifts in linguistic preferences, market needs, and ideological environments over time. Self-retranslation-when translators revise their own prior work-remains an uncommon and understudied phenomenon. This research examines five English novels that received second Chinese translations by their original translators 8-27 years after initial publication. Using an AI-assisted annotation system, we identified 89,175 changes across lexical, syntactic, semantic, pragmatic, and orthographic dimensions, and developed two measurement tools: the Fidelity Index and Audience-Accommodation Index. The data shows newer translations typically increase source-text fidelity, supporting the Retranslation Hypothesis, though with significant variations between works. We propose the Iterative Self-Retranslation Process (ISRP) model to explain these differences, connecting revision patterns to five factors: translator expertise development, changing linguistic norms and technologies, market influences, reader response, and sociopolitical environments. The study's methodology, along with the developed indices and model, offers a replicable framework for future research and equips researchers, translators, and publishers with practical tools for editorial planning.
The use of MT tools is typically covered in translation technology courses, but with the significant advances in AI-based MT and the ubiquitous presence of MT tools, issues relating to MT inevitably also arise in practical translation classes. This paper focuses on exploring how MT literacy can be incorporated into a specialized translation class. By contrasting trainee translators' performance in post-editing and translation, the study examines which aspects of MT literacy emerge as particularly relevant. In addition, the participants' views on the post-editing and translation assignments are compared. The results reveal that while MT output can be useful to trainee translators faced with a demanding source text, the benefits of MT tools coexist with challenges. Addressing issues relating to comprehension, terminology and rhetoric, five aspects of MT literacy that need to be addressed in a specialized translation class are identified. The findings suggest that the integration of MT literacy into specialized translation courses is crucial for successful use of MT tools in translation.
