The integration of national capacity and translation capacity has given rise to the novel concept of “National Translation Capacity” (NTC), thereby opening a new research avenue for modern translation studies. NTC not only represents a conceptual expansion of both national capacity and translation capacity, but also signals a convergence of perspectives between pragmatic translation studies and national development studies in the new era. Despite nearly five years of development and the generation of numerous significant research outcomes, as an emerging agenda, NTC naturally entails certain issues that urgently require clarification and refinement. These primarily encompass its disciplinary positioning, the demarcation of its research boundaries, and the elucidation and realization of its systemic functions. This paper argues that the disciplinary affiliation of NTC should be firmly anchored within translation studies, its categorical boundaries should center on translation capacity, and its systemic functions should place greater emphasis on its differentiating function.

In 2022, Regional and Country Studies was officially established as an independent first-level discipline in China, making the design of talent cultivation programs an urgent task for relevant universities. Taking Korea University in the Republic of Korea as a case study, this paper examines its relatively mature talent cultivation system for Regional and Country Studies from multiple dimensions, including major setup, degree levels, curriculum design, course resources, faculty development, training models, and university-enterprise cooperation. On this basis, the paper proposes an optimized model for talent cultivation in China’s Regional and Country Studies. First, construct an integrated tiered curriculum system spanning bachelor’s, master’s and doctoral stages; second, build a diversified teaching team, exploit cross-university curriculum resources and conduct categorized talent training; third, take project-based talent training as the core carrier to build an industry-education integrated practical training system; fourth, set up overseas internship and practical training bases to boost the collaborative development of industry, academia, research and application. These measures are intended to provide a scientific theoretical reference and practical enlightenment for talent cultivation of Regional and Country Studies in China.

Generative artificial intelligence (GenAI) has attracted widespread attention across the humanities and social sciences. Drawing on insights from ethics, the philosophy of technology, and technology ethics, this study constructs a three-dimensional analytical framework of “human-data-society” to systematically examine the ethical risks of translation technologies in the context of GenAI. At the human-machine relationship level, the risks involve translator identity shift and ambiguous copyright ownership; at the data governance level, the risks include privacy breaches, information distortion, and algorithmic bias; and at the societal impact level, the risks manifest as resource monopolization and linguistic homogenization. In response, this study advocates a threefold governance path of “human-machine collaboration, data co-governance, and joint ethical construction”, aiming to provide actionable policy recommendations and theoretical support for the regulation and sustainable innovation of translation technology ethics.

The advent of generative AI, with its advanced machine learning and natural language processing capabilities, presents transformative opportunities for the translation service industry, translation education, and other sectors, while also introducing significant security risks. In the era of generative AI, translation security risks are characterized by multiplicity, embeddedness, and ubiquity, which pose great challenges to translation security governance. Based on an analysis of the sources and characteristics of translation security risks in the era of generative AI, this paper proposes the following governance strategies: adhering to a holistic view of national security, balancing comprehensive demands such as technological value creation, sensitive data protection, and national security maintenance, and adopting a governance model that integrates technology, education, and institutions. Priority should be given to technological solutions such as AI and blockchain to address technical problems, and efforts should also be made to strengthen science popularization and professional education to raise the public’s awareness and enhance their security capabilities in the use of generative AI translation. Furthermore, policy and legislative measures should be considered to control governance costs and improve governance effectiveness.

While large language models (LLMs) have significantly enhanced the efficiency of external-facing state translation, they concurrently introduce security risks such as information leakage and corpus bias. To address these challenges, this study develops a security assurance framework centered on technological governance. The research first establishes a state translation risk matrix, which systematically identifies and prioritizes four categories of risks — political, cultural, technical, and ethical — across three dimensions: data, algorithms, and application. Building upon this analysis, an integrated digital resource platform is proposed as the core governance pathway. The platform involves: (1) the on-premises deployment of an LLM, which is fine-tuned using domain-specific corpora to serve as the core machine translation engine; (2) the integration of Retrieval-Augmented Generation (RAG) technology, linking knowledge bases and terminological knowledge bases constructed from expert experience to enable precise and controllable knowledge supply; and (3) the implementation of a human-in-the-loop workflow to interactively revise the model’s outputs, thereby effectively mitigating risk-prone expressions. This proposed solution reconciles the powerful capabilities of LLMs with national security requirements, providing a manageable and iterative infrastructure for safeguarding national discourse security and preserving cultural sovereignty in the era of generative artificial intelligence.

Academic procrastination and foreign language anxiety (FLA) are prevalent cognitive-behavioral and affective challenges in college English learning. While their close correlation has attracted academic attention, existing studies have predominantly relied on static correlation analysis, leaving the dynamic covariation mechanisms underexplored. Furthermore, the lack of mixed-methods designs combining quantitative and qualitative approaches limits practical support for stratified instruction and precision intervention in college English education. Guided by Complex Dynamic Systems Theory, this study employs a mixed-methods design integrating latent profile analysis (LPA) and retrodictive qualitative modeling (RQM) to systematically investigate 695 college English learners. The results indicate that: (1) Five profiles were identified based on levels of procrastination and anxiety, with the “High Procrastination & High Anxiety on Core Tasks” group emerging as the most prevalent at-risk population. (2) The interaction between the two constructs is shaped by multi-level factors, including individual, classroom, and institutional dimensions, forming a mutually reinforcing bidirectional dynamic feedback loop. This study reveals the dynamic covariation mechanisms between academic procrastination and FLA, provides empirical evidence for affective and behavioral interventions in college English teaching, and offers a methodological reference for mixed-methods research in the field of foreign language education.

Against the backdrop of English as a lingua franca (ELF) increasingly becoming the dominant mode of international communication, English users’ identity perceptions and language practices have shown a trend toward diversification. However, systematic empirical research on ELF identity types among Chinese English majors remains relatively limited. As a mixed-methods approach that integrates both emic and etic perspectives, Q methodology is particularly effective in uncovering the internal structure of individuals’ subjective cognition. This study employed Q methodology to examine English majors’ ELF identity profiles and their influencing factors. The findings identified three distinct ELF identity profiles: instrument-oriented users of standard English, culture-oriented ELF users, and ambivalent multilingual users of English. These profiles were primarily shaped by sociocultural contexts, significant others, and individual factors. This study not only contributes to empirical research on ELF identity in the Chinese context but also offers insights for foreign language education and the development of intercultural competence.

The digital transformation of education driven by generative artificial intelligence has rendered intelligent technological, pedagogical, and content knowledge (iTPACK) a core issue in the professional development of foreign language teachers. Rooted in complexity theory, this study selects 103 secondary school English teachers as research participants and adopts the fuzzy-set Qualitative Comparative Analysis (fsQCA) method to explore the configurational correlations and effect characteristics among emotional labor, motivational beliefs of technology use, and iTPACK construction. The empirical results identify three types of pathways that facilitate the effective construction of iTPACK and two types of pathways that constrain its development, demonstrating the inherent characteristics of asymmetry, equifinality, and conditional complementarity in the process of iTPACK construction. By revealing the configurational effects of iTPACK construction from the dual perspectives of emotional labor and motivational beliefs of technology use, this study expands the dimensionality of complexity-related research within iTPACK theory. It also validates the methodological value of configurational analysis in interpreting the complex psychological mechanisms of teachers’ professional development and offers configurational intervention strategies for AI-integrated teacher training in foreign language education.

As China advances the construction of its foreign-related rule of law, high-quality court interpreting in criminal trials serves as a pivotal pillar for enhancing the international credibility of the Chinese judiciary and shaping the image of the “Rule of Law in China”. Addressing prevalent issues in current foreign-related criminal trials, such as the absence of an official interpreter accreditation system, the lack of standardized working guidelines, inadequate quality assessment mechanisms, and the ambiguity of rights and responsibilities, this study draws on translation ethics theory to construct an ethical framework for court interpreting in criminal trials. This study first elucidates the field attributes and ethical connotations of court interpreting in criminal trials, then establishes three core principles: fidelity and accuracy, neutrality and impartiality, and professional accountability. Based on these principles, the study constructs an integrated ethical system unifying institutional, procedural and professional ethics. Finally, from a practical perspective, three implementation paths are proposed: internalizing professional ethics through an optimized education system, regulating procedural ethics via courtroom guidelines, and perfecting institutional ethics through governance mechanisms. This study seeks to provide theoretical underpinnings and practical guidance for ensuring procedural justice and protecting the rights of parties in foreign-related criminal proceedings.