From the Source roundup – July 2026
Welcome to this month’s “From the Source” roundup
From the Source is a regular feature on the podcast I make called Source 2 Target. Each week, I summarise the key points from a peer-reviewed article in the world of translation research on the podcast’s LinkedIn. But as not everyone is on the platform or following the show, I share an even shorter version of last month’s articles here. You can also read the full versions on the LinkedIn feed or Instagram.
So here goes!
Are non-professional subtitlers less creative than professionals?
Samani, E.; Badiozaman, F. & Bagheripou, R. (2024), A Corpus-Based Approach to Creativity in Non-Professional Subtitles: The Case of Hapax Legomena, New Voices in Translation Studies, 29 (1)
Non-professional subtitlers, often described as fan-subbers, are usually associated with greater freedom and creativity than professional subtitlers, especially in the visual layout of subtitles. Because they work outside formal training and established industry conventions, it is often assumed that they are also more creative in their translation choices. However, the study discussed here questions that assumption. The researchers examined a large sample of unofficial Persian subtitles for American comedy films. They focused on the rarest words in the corpus and analysed the translation strategies used, classifying them according to Kussmaul’s typology of creative and non-creative translation strategies. The results showed that the fan-subbers relied on non-creative strategies 69% of the time, while creative strategies accounted for only 31%. Although the study is limited to one language pair and one genre, its findings are significant because they challenge the idea that lack of professional training automatically leads to linguistic creativity. Instead, the results suggest that real creativity in translation may depend on expertise. To bend or break translation rules effectively, subtitlers may first need to understand those rules, rather than simply operating outside them.
How do clients decide whether to use machine translation or not?
Nitzke, J., Canfora, C., Hansen-Schirra, S. & Kapnas, D. (2024), Decisions in projects using machine translation and post-editing: an interview study, The Journal of Specialised Translation, 41, 124-148
The article looks into how commissioners of translation projects decide whether to use neural machine translation (NMT). The researchers created a decision-tree-style model and tested it through interviews with real translation commissioners to see whether it reflected practical decision-making. Unsurprisingly, many interviewees identified the quality of the final target text as the most important factor, while risk, including cybersecurity concerns, also played a significant role.
Some findings were less expected. NMT appeared to be used less often in the high-end translation market than anticipated. More notably, commissioners seemed to make strategic decisions about using machine translation for certain text types or clients, rather than assessing each project individually. The author suggests this may have important implications for how translation professionals discuss technology with clients, though the practical consequences remain uncertain.
The passage also addresses the idea that discussions about machine translation may now seem outdated because attention has shifted to artificial intelligence. However, the author argues that the underlying question remains similar: whether and how to use automated translation technologies responsibly. AI may attract more hype than NMT, but it brings its own problems. Therefore, client-centred decision models remain valuable for both MT and AI.
Is GenAI changing the way translators think?
Zheng, Z. (2025), Theoretical insights and empirical findings on metacognition in translation: a review and conceptual framework, Discover Psychology, 5
This article suggests that translating machine-generated content may involve different mental processes from translating from scratch. The main aim was not directly to compare these two modes of work, but to develop a framework for describing translators’ metacognitive processes – in other words, how translators think about and regulate their own thinking while working.
The proposed Translation-Specific Metacognitive Strategies Framework divides the translation process into three broad phases: pre-translation, in-translation and post-translation. These correspond roughly to planning, monitoring and evaluation. However, the passage stresses that the process is more complex than a simple sequence of stages. Skilled translators continually move between these strategies, drawing on planning, monitoring and evaluation throughout their work.
The key question raised is whether post-editing machine-generated drafts disrupts these metacognitive flows. Because machine translation or generative AI produces a draft instantly, translators may miss out on important planning and monitoring stages that normally occur when translating from scratch. This could potentially affect translation quality, although the passage notes that more research is needed.
Overall, the framework is useful because it gives translators a clearer way to discuss how their minds work and how new technologies may be changing translation practice.
How do translators deal with non-binary gender identities in heavily gendered languages?
Lardelli, M., Primorac Aberer, Z. & Hiebl, B. (2025), Gender-Fair Audiovisual Translation: First Considerations on How to Address Non-Binary Genders, The Journal of Specialised Translation, 44
How do translators represent non-binary identities in languages whose grammar is strongly based on binary gender? In short, badly.
The article examines how subtitles and dubbing handled non-binary characters in German, Italian, and Croatian. The researchers found mixed results: some translations respected non-binary identities, many could have been improved, and some misgendered the characters entirely.
Part of the challenge comes from heavily gendered grammatical systems and the absence of widely accepted gender-inclusive conventions in some languages. Audiovisual translation also faces practical constraints such as subtitle length and lip synchronisation. However, the authors argue that the main problem is a lack of institutional support, professional training, and clear guidelines for translating non-binary language.
To address this, they call for better access to source materials and contextual notes, as well as glossaries and style guides developed with the involvement of non-binary people. They also recommend stronger attention to gender-fair language in translator training and greater accountability from media platforms that publish subtitles and dubbed content.
The article concludes that as non-binary representation grows in global media, translation must evolve to affirm these identities rather than erase them, making translation a matter of both language and social justice