Institute of English Studies · University of Łódź
Current editorial and infrastructure initiatives in translation and interpreting studies.
Digital technologies have been reshaping translator and interpreter training, creating an urgent need for innovative pedagogical approaches that address both the opportunities and psychological challenges of technological integration. While technology is a key driver, this Special Issue foregrounds digital anxiety and resilience as broader professional constructs shaped not only by tools but also by industry collaboration, sustainability, and the everyday realities of professional practice.
As training programmes increasingly incorporate sophisticated digital tools and platforms, educators observe a range of psychological reactions among students, early career and experienced professionals, and educator practitioners, from enthusiasm to apprehension. These reactions, which can collectively be referred to as technological, or 'digital anxiety,' have highlighted the need for building 'digital resilience' (Kornacki & Pietrzak, 2024).
One of the goals of this Special Issue is to explicitly frame digital anxiety and resilience as pedagogical constructs, which sets it apart from ITT's Special Issues on AI (2025) and value(s) (2027) by putting educational design and measurable psychological outcomes at the forefront of translation and interpreting practice.
Digital anxiety in translator and interpreter education has been defined as the stress and unease that students, novice and experienced translators and interpreters, and educators experience as technology—with recent acceleration driven by AI and workflow automation—rapidly transforms their profession (Kornacki & Pietrzak, 2024). This anxiety manifests in various forms:
Professional conditions—such as client relations, platformisation and precarity, assessment and accreditation pressures, and emerging sustainability expectations—can amplify anxiety even when specific tools are not the proximate cause.
In contrast, digital resilience is understood as students' and graduates' capacity to adapt and thrive in an increasingly technology-oriented profession. Resilience encompasses not only competent technology use but also professional agency and wellbeing: boundary setting, ethical decision making, collaborative practices with industry partners, sustainable workload and workflow design, and reflective habits that support long-term employability.
The Special Issue welcomes research-based contributions on teaching and learning in the digital age, including:
| Abstracts due: | 19 December 2025 |
| Abstract acceptance notifications: | End of March 2026 |
| Full papers due: | 30 September 2026 |
| First-round peer review: | September–November 2026 |
| Round 1 decisions to authors: | End of January 2027 |
| Revised papers due: | End of March 2027 |
| Second-round peer review: | March–May 2027 |
| Final versions due: | End of June 2027 |
| Expected publication: | 2028 |
Translation and interpreting scholarship is dispersed across hundreds of journals, edited volumes, and conference proceedings. Finding what specific researchers have actually claimed — not what someone remembers them saying — means retracing the same literature searches, opening the same PDFs, scanning the same pages. The knowledge is there, but it is not navigable.
The project rests on a single YAML knowledge base that stores each claim as a complete, self-contained proposition with its full citation chain. Every entry includes the original wording (for direct quotes), the claim type (authorial assertion, empirical finding, theoretical position), thematic tags, and a unique identifier for cross-referencing.
Sources move through a six-gate protocol before entering the knowledge base. First, the text is mapped for claim-rich zones — sections where authors stake positions or report findings. Each candidate claim is then validated against the source: does it stand alone as a complete proposition? Is the supporting citation verifiable? Does it duplicate an existing entry? Validated claims receive semantic tags drawn from a controlled vocabulary covering methodological approaches, translation modalities, and theoretical frameworks. Only then does the entry append to the knowledge base.
One persistent risk was paraphrase drift — the tendency to summarise claims into generic statements that lose their analytical edge. The protocol addresses this by requiring verbatim capture for any claim that will be quoted directly, and by cross-checking paraphrased entries against the source before finalisation.
Duplicate detection presented another challenge. Sources often overlap in edited volumes or reprinted collections. Without systematic tracking, the same claim could enter the knowledge base multiple times with different IDs. The manifest system maintains source-level records, flagging duplicates before they reach the extraction phase.
Deferred processing was necessary for sources with complex structures — edited volumes where chapter boundaries blur, or texts with substantial bibliographic apparatus that requires separate handling. These go into a pending queue rather than blocking the main workflow, allowing the system to maintain momentum while preserving integrity.
The knowledge base is accessed through a lightweight browser interface: keyword and semantic search, filter by topic or method, jump straight to sources. No server required — it runs entirely client-side, which means data stays local and the tool travels with the repository.
In the 1960s, Kelly Johnson, lead engineer at Lockheed's Skunk Works, challenged his teams to build aircraft that an ordinary mechanic could repair on a battlefield with common tools. The principle — 'Keep It Simple, Stupid' — has since travelled far beyond aeronautics. An earlier echo even appeared in a 1938 Minneapolis editorial urging that a city charter be 'condensed and simplified' so citizens could actually understand it. The lesson holds: complexity is the enemy of reliability.
An agentic system is a network of specialised modules — each handling a distinct task, passing outputs to the next, coordinated by a central orchestrator. The temptation is to make each module brilliant: multi-layered reasoning, recursive self-checks, exhaustive fallback chains. But every added layer is a new failure surface.
The KISS rule demands that each component do one thing, do it transparently, and hand off cleanly. A module that validates citations should validate citations — not philosophise about epistemology. An orchestrator that routes tasks should route tasks — not attempt to rewrite the task mid-flight. Complexity is permitted only when it carries a distinct, documented responsibility that simpler forms cannot achieve.
This principle is tested continuously. When a research pipeline spans literature intake, claim extraction, knowledge-base population, and wiki synthesis, each handoff must be explicit: who receives what, under what conditions, with what confirmation gate. Implicit assumptions between modules are where systems silently fail.
Gall's Law states that a complex system that works is invariably found to have evolved from a simple system that worked. Start with a pipeline that functions on a single paper. Add a gate only after a real failure. Build the encyclopedia only after the index works. The discipline is not austerity — it is patience.
Gall, J. (1977). Systemantics: How systems work and especially how they fail. Quadrangle/The New York Times Book Company.
Johnson, C. L. 'Kelly', & Smith, M. (1985). Kelly: More than my share of it all. Smithsonian Institution Press.
The Minneapolis Star. (1938, December 2). Keep it short and simple. Newspapers.com. https://www.newspapers.com/article/the-minneapolis-star-keep-it-short-and-s/38577884/
A forthcoming special issue addressing themes in language studies.