Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
16504 papers
The present study extends recent work on Universal Dependencies annotations for secondlanguage (L2) Korean by introducing a semiautomated framework that identifies morphosyntactic constructions from XPOS sequences and aligns those constructions with corresponding UPOS categories.We also broaden the existing L2-Korean corpus by annotating 2,998 new sentences from argumentative essays.To evaluate the impact of XPOS-UPOS alignments, we fine-tune L2-Korean morphosyntactic analysis models on datasets both with and without these alignments, using two NLP toolkits.Our results indicate that the aligned dataset not only improves consistency across annotation layers but also enhances morphosyntactic tagging and dependency-parsing accuracy, particularly in cases of limited annotated data.
In recent years, small Large Language Models (sLLMs) have increasingly been recognized for their utility due to their cost-effective performance in generating high-quality responses without relying on cloud APIs that may pose privacy concerns. This study conducts a comparative ablation analysis to evaluate the hedonic valence rating capabilities of three distinct models: Llama3.2, Phi-4, and nomic-embed-text-v1.5. The investigation involves assigning valence ratings on a 9-point scale to 140 words sampled from an extensive human-rated dataset, a subset of which was used in a previous study. The chatbot models, Llama3.2 and Phi-4, were employed via ollama using prompts specifically engineered to solicit emojis and numerical valence ratings. Nomic embeddings were used in a linear regression between the word embeddings and the human ratings. Statistical analysis revealed significant correlations between the models’ outputs and human ratings (p-value ≤ 0.001). Despite limitations, these results underscore the potential of sLLMs and embedding models in enhancing sentiment analysis. This study shows how sLLMs can effectively approximate word valence and may help in linguistic research.
This manuscript proposes the S M Nazmuz Sakib Dependency-Focus Principle for Bengali sentence structure and introduces a derived scalar quantity, the Sakib constant, defined over dependency treebanks. Informally, the principle states that in attested Bengali usage, core arguments (subjects and objects) cluster closer to the verbal head than peripheral modifiers (adverbials and clausal adjuncts), and that the ratio between these average distances is numerically stable across corpora. Using real statistics from the UD Bengali-BRU treebank and the Bengali section of the Bengali-Magahi PUD treebank, we define the Sakib constant K Sakib as the ratio between average dependency lengths of core versus peripheral relations, and compute its value for UD Bengali-BRU. Ten figures based on genuine counts and averages illustrate tense and case distributions, relation frequencies, and core versus non-core dependency lengths for Bengali and, for comparison, Magahi. The proposal is presented as a precise hypothesis, mathematically well-defined and empirically grounded in existing treebank data, but still requiring broader testing for confirmation and cross-linguistic generalisation.
This article is dedicated to the description of the morphological features of the Romanian language of the 16th-17th centuries, using the manuscript Codex Neagoeanus as an example. The subject of the research is a comprehensive morphological analysis of the manuscript monument "Codex Neagoeanus" (ms. rom. 3821, Romanian Academy Library), dated to the beginning of the 17th century. This codex represents a characteristic collection of religious and folk texts (cărți populare) typical for Romanian culture of the 16th-17th centuries, including translations of a popular romance, a didactic treatise, a brief nomocanon, and works of astrological literature. The study focuses on a systematic description and classification of archaic and variable morphological features of the Romanian language recorded in the texts of the codex. Special attention is given to those features that demonstrate the transitional nature of the language of this era, which is at the intersection of the old Latin tradition and the active influence of Slavic languages, as well as the process of establishing future literary norms. The analysis is conducted using material from all significant parts of speech: nouns, adjectives, verbs, pronouns, and adverbs. The main research method is a comprehensive morphological analysis aimed at identifying and classifying characteristic archaic and innovative elements in the morphological system of the writing monument. Paleographic analysis methods are also employed. The scientific novelty of the research lies in the first detailed and systematic linguistic analysis of Codex Neagoeanus, which introduces new factual material into scientific circulation. Key conclusions include the following: the morphological system of the codex is characterized by extreme variability and the absence of a stable norm, which is manifested in the coexistence of archaic (ending -u for masculine nouns, obsolete forms of the perfect tense) and innovative (periphrastic conditional) forms. It has been established that phonetic processes (e.g., diphthong contraction ea) directly influenced verb conjugation paradigms. An important conclusion is the demonstration of the deep integral influence of Slavic languages, expressed not only in lexical borrowings but also in the active use of Slavic word formation models (suffixes -enie, -nie, prefix ne-) to create new words based on Latin and Greek roots. Thus, the codex serves as a vivid testimony to the complex and multifaceted state of the Romanian language in the early period.
Language functions as a medium of communication that enables individuals to interact within their social environment. Proper and correct Indonesian refers to the use of the language in accordance with prevailing social norms and linguistic rules. However, the use of Indonesian in newspapers often demonstrates deviations from these norms. This study aims to describe the grammatical errors found at the sentence level in opinion articles published in Harian Analisa. The research employs a qualitative descriptive method, with data obtained from selected opinion texts in the newspaper. The data were analyzed using descriptive analysis techniques based on Purwandari’s linguistic theory. The findings reveal seven main types of sentence errors: (1) completeness, (2) parallelism, (3) conciseness, (4) coherence, (5) variation, (6) diction accuracy, and (7) spelling accuracy. The study concludes that the Indonesian language used in Harian Analisa opinions still requires improvement in syntactic and lexical accuracy. These findings are expected to serve as a reference for enhancing public awareness of proper and correct Indonesian language use in written media.
The article examines the interconnection between culture, ideology, and translation, emphasizing their influence on modern translation studies and the translator's decision-making process.It explores how cultural and ideological factors shape translation strategies, affecting both textual interpretation and audience perception.The study highlights that translation extends beyond linguistic equivalence, functioning as a mechanism for cultural representation and ideological negotiation.Special attention is given to the role of culture in translation, including its impact on social norms, historical traditions, and artistic expressions.The article underscores the challenges translators face when dealing with culturally specific elements, such as folklore, customs, and symbolic references, which may not have direct equivalents in the target language.The translator's choice between domestication and foreignization is analyzed, illustrating how translation either preserves cultural uniqueness or adapts content for better audience accessibility.These decisions ultimately shape how cultural identity is transmitted across languages.The article explores as well the ideological dimension of translation, demonstrating how political, institutional, and editorial influences affect the selection of words, rhetorical structures, and textual modifications.It is shown that translation is not a neutral act but rather a process of ideological mediation, where even minor linguistic adjustments can alter the ideological message of a text.The study examines how ideology manifests in translation through censorship, selective omissions, lexical choices, and discourse framing, all of which contribute to shaping public perception.The research further discusses how culture and ideology often overlap in translation, creating a complex interplay that affects textual meaning.Translators must navigate ethical and communicative dilemmas, ensuring accuracy while considering socio-political implications.The study concludes that understanding the dual influence of culture and ideology is essential for producing translations that are not only linguistically accurate but also contextually and ideologically aware.Future research may focus on developing strategies to balance cultural authenticity and ideological representation, particularly in the context of globalization and digital media.Key words: culture, identical/
Artificial Intelligence (AI) refers to systems that can perform tasks that typically require human intelligence, such as learning from data, understanding natural language, recognizing patterns and making decisions (Russell and Norvig, 2009). Unlike traditional computer programs that follow explicit instructions, AI systems are featured in digesting big data, adapting to new inputs and improving performance over time. At its core, AI is powered by algorithms that are sets of mathematical and logical instructions specifying how computers analyze information and make decisions. Modern AI relies on deep learning techniques, particularly massive neural networks, to process complex and high-dimensional inputs such as images, speech and natural language and extract patterns from relevant big data (Mienye et al., 2024; Razavi, 2021). The rapid-evolving generative AI represents a signature move of contemporary AI paradigms (Sengar et al., 2024). Tremendous industrial and academic resources have been investing to advance AI alignment, interpretability and efficiency and seek to balance innovation with safety, transparency and responsible deployment across global industries.In the context of the sport business, AI is not just a technological add-on but a transformative force that provides the tools to analyze complex data, automate operations and create new value for fans and stakeholders. This deep connection extends to sport business research, where AI has been reshaping how sport business knowledge is created, validated and applied. The impact of AI on sport business research can be understood from forging novel research agendas, advancing methodological paradigms and improving research efficiency.The most profound impact of AI is its role as a catalyst for novel research agendas. As AI technologies become deeply embedded in the everyday lives of sport consumers and rapidly reshape the operations of sport organizations, they create emergent phenomena that existing theories may not adequately explain. This presents fertile ground for sport business researchers to explore, potentially leading to conceptual refinements and the development of entirely new theoretical frameworks. Below we outline several research agendas for sport business scholars engaging with AI.How Fans Respond to Sport Products Integrating AI. Sport products are increasingly AI-supported, where AI serves as a supplemental component to enhance existing functions or even AI-powered, where AI acts as the core engine of the product itself (Naeem et al., 2024). This AI transformation ranges from the integration of AI for enhancing traditional game-day experience to the full adoption of AI in delivering personalized content recommendation, powering emerging sport-betting platforms and revolutionizing chatbot-based interactions. A new field of research is emerging to explore the psychological and sociological dimensions of how sport consumers interact with AI. This line of inquiry could further refine the conceptual models in the field or even lead to new theoretical frameworks explaining human–AI dynamics.How sport businesses utilize AI. The deployment of AI is reshaping sport organizations by transforming both day-to-day operations and high-level strategic roles, including but not limited to public relations, marketing planning, resource allocation, talent management and organizational design. As AI assumes a more central role in shaping strategy and governance, sport organizations may need to adapt their culture, capabilities and decision structures to remain competitive. A growing body of research aims to assess the effectiveness of adopting AI technologies in organizational operations and strategic management and explore organizational structures needed to address the challenges of AI transformation.How governing bodies and society adapt. The prevalence of AI raises significant questions for governance and ethics. Critical frontiers for research include investigating algorithmic bias in fan profiling, ensuring data privacy and establishing fair regulations for AI in sports betting. This line of inquiry is essential for developing new governance models and ethical guidelines for the sport industry.Sport business research has progressed from employing AI primarily as an analytical tool or methodological enhancement to developing AI-centered research agendas that examine how key stakeholders respond to various applications of AI in the sport industry. At present, consumer responses have received greater scholarly attention, whereas the perspectives of business entities and the implications for governance and policy remain comparatively underexplored.Beyond creating new topics, AI is reshaping the methodology of sport business research. It provides powerful new ways to advance existing research agendas by advancing data variety, data volume, data collection, analytics and experiment simulation, which benefits both correlational and experimental studies.Augmented data features. With the assistance of natural language processing (NLP) and computer vision, researchers are no longer limited to structured numerical data such as surveys and official statistics. We now can tap into vast and varied unstructured data sources like natural language from social media, images from fans and video feeds from games. The data with high breadth, granularity and contextual richness enable extraction of sentiment, emotion, contextual meaning and relationships that traditional datasets could not capture (Mao, 2025). The volume and velocity of available data have expanded exponentially, offering a richer, more holistic view of the sport ecosystem (Mamo et al., 2022).New quantitative solutions. Machine learning and language processing models provide powerful additions to the researcher's arsenal, which largely enhance our capacity for analyzing complex unstructured data, modeling non-linear relationships, uncovering latent structures and elevating prediction power that are challenging to achieve with the traditional analytics paradigm. AI can also assist in cleaning and pre-processing large datasets, detecting anomalies and suggesting data transformations. The analytical advancement empowers researchers to develop conceptual models or test established theories with a level of rigor and predictive accuracy that was previously impossible (Chen and Chen, 2024).AI-enhanced qualitative approaches. AI and NLP have also transformed traditional qualitative research methodologies, significantly expanding researchers' ability to process large-scale textual data and automate time-intensive coding processes (Hitch, 2024). They help researchers identify thematic patterns across extensive textual corpora, facilitate rapid comparison across multiple data sources and enhance reproducibility of interpretive analysis in ways that manual approaches often fall short of (Nelson, 2020). This paradigm shift allows researchers to engage with both the breadth and depth of consumer experience simultaneously (Mao et al., 2024).Innovative computational simulation. AI facilitates the creation of sophisticated simulations that explore and examine the behavior of key stakeholders (e.g. fans, athletes, sport organizations and general businesses) within sport business ecosystems. Notably, generative AI gives researchers unprecedented power to design and tailor realistic experimental stimuli such as synthetic commentary, virtual sport environments or tailored promotional messages, enhancing the rigor and ecological validity of experimental designs.AI also benefits sport business research at a broad level by reshaping and streamlining fundamental early-stage tasks, thereby improving research workflow efficiency and enabling scholars to devote more time to higher-level analysis and interpretation. For example, AI-powered platforms such as Semantic Scholar and Sourcely have significantly improved the efficiency of literature review and information search, sorting and synthesis. These tools interpret the context of queries rather than relying solely on keywords, automatically identify related papers, summarize key findings and generate conceptual maps of research areas, enabling scholars to more quickly evaluate existing literature and identify gaps. By automating these foundational tasks, AI not only improves efficiency but also enhances reproducibility in the iterative research cycle where new knowledge builds upon prior work.Five studies in this special issue explore consumer response to AI transformation in various sport consumption settings, ranging from the deeply personal (AI-supported wearable devices) and the interactive (AI chatbots) to the persuasive (generative AI in ads) and the high-stakes (AI-driven sports betting). This collection of work provides crucial managerial implications for navigating the AI transition and enriches theoretical frameworks by illuminating the complex factors, such as emotion, technology anxiety, perceived trust and subjective norms that ultimately determine consumer adoption.Lee et al. (2025) investigated how consumer evaluations of AI-generated sports ads are affected by AI awareness timing, advertisement model type and source-message incongruence. The results show that AI awareness generally have a positive impact, particularly when consumers are aware of the AI's role after viewing the ads. Virtual Human models are rated the lowest compared to Digital Twin and Human models and source-message incongruence negatively influenced evaluations. The study offers insights for practitioners on optimizing AI ads by strategically timing disclosures and selecting appropriate models and provides references for effective AI integration in sport advertising practices.Gerke et al. (2025) empirically examined consumer responses to the AI-supported wearable devices based on the Artificially Intelligent Device Use Acceptance Model (AIDUA). Their findings highlight a significant intention–behavior gap, as emotions were found to predict the intention to use but not actual consumption. The study also nullified a common assumption that consumers' appraisal of AI anthropomorphism influences their performance or effort expectancies. These insights are critical for sports managers and marketers aiming to improve the adoption of AI-supported sports services.Grounded in the parasocial interaction and the social exchange theories, Choi and Lee (2025) investigated how anthropomorphized AI chatbots in sports enhance social presence to boost consumer loyalty and reduce technology anxiety. Key findings indicate that anthropomorphism successfully increases social presence, which in turn positively influences loyalty while negatively affecting technology anxiety. This study also identifies technology anxiety as a partial mediator, showing that a heightened social presence can mitigate anxiety's negative impact on user loyalty. This research effort extends theory by demonstrating that social presence is a key mechanism for reducing user anxiety, offering practical insights for sports marketers using AI to enhance consumer engagement.Buechner et al. (2025) scrutinized whether the source of a sports betting recommendation (AI or human) affects consumer perceptions of expertise and their likelihood to follow the advice. Through three lab experiments, this research consistently found that compared to human resources, AI recommendations significantly decreased consumers' perceptions of expertise. This lower perceived expertise in turn reduced participants' likelihood of following the betting recommendation. As one of the pioneer studies in this area, the findings suggest that despite technological advances, consumers currently exhibit lower trust in AI for sports betting advice, perceiving human sources as more credible.Dinç et al. (2025) assessed ChatGPT adoption's impact on soccer bettors' behavioral intention and word of mouth. Survey results show that attitude and subjective norms are strong predictors of behavioral intention. Specifically, perceived ease of use and usefulness positively shaped attitude. The effect of usefulness on intention was indirect, mediated entirely by attitude. Social influence significantly drove word of mouth via subjective norms and behavioral intention. This research broadens the applicability of existing theoretical frameworks by examining AI adoption among soccer bettors, while simultaneously offering AI developers actionable strategies to improve user acceptance within this evolving market.Perspectives on how sport organizations utilize AI show organizations' capacity to digest AI techniques to compete, profit and grow in today's market. This research body is essential for understanding the strategic, operational and economic implications of AI in the sport ecosystem. The current special issue highlights two studies by five scholars.Du et al. (2025) examined whether AI can assist in training sports salespeople by evaluating their interactions with prospective ticket buyers. Using topic modeling and sentiment analysis on transcribed National Basketball Association (NBA) sales calls, the research identified several key predictors of success. Findings show that agents with greater lexical diversity and a moderate speaking pace generated more positive customer sentiment and achieved higher sales success. Additionally, a positive association was found between asking more open-ended questions and effective information gathering. Guided by the Technology-Task-Fit theory, this study provides evidence that AI can effectively analyze sales conversations to deliver applicable, data-driven feedback, supporting its integration into modern salesperson training programs.Fortunato and Kosterich (2025) examined how Amazon Web Services (AWS) uses its functionally congruent sponsorship with the National Football League (NFL) to demonstrate its performance capabilities. AWS provides both on-field (e.g. player health and safety) and off-field (e.g. game scheduling) services to the NFL and promotes this deep integration via major marketing communications (e.g. AWS websites, in-game elements and TV commercials) to showcase its brand reliability, which is a key factor in business-to-business marketing. The core message of sponsorship implies that if AWS can handle complex tasks for the NFL, it can certainly do the same for a potential client's business. This study provides a timely, practical example of how AI brands leverage sports sponsorship to communicate and position their advanced technical services.As previously discussed, AI is largely reshaping the sport data frontier, altering data attributes (variety, volume and velocity), collection methods, analytical routines and experimental simulation. The ripple effects of this data revolution on sport business research are profound and pervasive. This impact is comprehensively exemplified by four articles featured in the current special issue.Anagnostopoulos et al. (2025) utilized natural language processing (GPT-4) to analyze how companies on the Qatar Stock Exchange reported their “corporate social responsibility (CSR) through sport” initiatives within annual reports from 2006 to 2022. By automating information retrieval from all 46 listed companies, the analysis identified 672 distinct CSRs through sport initiatives, revealing a significant upward trend over the period. The primary contribution lies in its human–AI framework, which provides a novel and efficient method for systematically analyzing how publicly listed companies communicate their CSR activities in the sport sector. This offers a new perspective on corporate philanthropy in the Middle East.Ryu et al. (2025) used AI to analyze how player performance in professional women's volleyball affects fan emotions, measured via sentiment analysis of Instagram comments. It also examined the moderating roles of superstar status and facial attractiveness. The results confirmed fan emotions are tied to game outcomes but revealed a complex beauty bias. Specifically, attractive players received a beauty premium (less negativity) for errors, yet faced a “beauty penalty” for scoring points, a dynamic not observed with non-all-star players. This research advances the use of AI to demonstrate how attractiveness moderates fan reactions to on-court performance, expanding prior work that focused primarily on off-court factors like salary.Bian and Cork (2024) developed a machine learning model capable of predicting the of and identified the key these machine learning for fan offers a data-driven to traditional The model identify sponsorship as the most by and fan The research provides a novel for understanding how fan are offering an actionable for practitioners to enhance sponsorship et al. (2025) the of sport consumption by consumers' perceived and This offers a data-driven method for understanding consumer in a by AI and deep learning approaches to analyze The study highlights that is by a of and social It provides foundational evidence and practical insights for brand managers navigating the sport and fan have become data sources et al., et al., of it which in turn AI data collection is more and as interaction by social and is to that could be used for marketing et al., 2021). This is further by a of through wearable technologies that extensive and behavioral data et al., The questions of data and the of and significant ethical and are to assess the evolving of fan and data as as of technological and frameworks be needed to of personal information in sport consumption. these represents an emerging yet essential of research, one with broad implications for the social between sport entities and their stakeholders in today's data-driven of algorithmic which refers to the systematically and outcomes by has been increasingly across and It can in of data resources, advertising and and impact et al., 2024). the sport AI particularly on datasets, may to and of the contemporary sport leading to or even and 2021). For an for results if it has not been adequately on the of the new and ecosystem. AI models may not the such as the rapid of sport betting or of fan or management tools to be based on an understanding of the market. most these algorithms can and even existing by an AI model for talent or fan marketing is on data that it bias its potentially leading to outcomes and the of from key sport agendas. when effects of AI it may on these the of bias in the AI of intelligence, and business presents a critical governance for the modern sport which is currently by a significant AI innovation is advancing more rapidly than the development of or 2024). 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The articles in this special issue have advanced this by and empirically examining key from sport AI The of AI and the relevant critical research in this as a for to further explore, and in sport business, the for transformation across the sport ecosystem. we like to our profound to all of the their time and expertise to this special Their and the scholarly of this special
В условиях стремительной цифровизации медиапространства и усложнения профессиональных требований к журналисту целью исследования явилось теоретическое обоснование и экспериментальная проверка эффективности интерактивных образовательных технологий в формировании речевой культуры студентов-журналистов. На базе факультетов журналистики трех гуманитарных университетов в 2019-2023 годах был проведен комплексный педагогический эксперимент с участием 342 студентов, разделенных на контрольные и экспериментальные группы; использовались системно-деятельностный и компетентностный подходы, стандартизированные тесты на владение языковыми нормами, контент-анализ медиатекстов, экспертные оценки редакторов и преподавателей, включенное наблюдение за речевым поведением на интерактивных занятиях, а также методы математической статистики (t-критерий Стьюдента, U-критерий Манна–Уитни, корреляционный и факторный анализ). В экспериментальных группах была реализована авторская модель, включающая кейс-стади, дебаты, ролевые игры, проектные формы работы, подкастинг, перевернутый класс, мультимедийные лонгриды и коллаборативные цифровые платформы редактирования текстов. Результаты показали статистически значимый прирост доли студентов с высоким уровнем нормативного компонента речевой культуры (с 11,9 до 34,2%) и сокращение доли с низким уровнем (с 38,8 до 12,4%) на фоне минимальных изменений в контрольных группах; зафиксировано существенное улучшение коммуникативно-прагматических умений (логичность и связность речи, богатство словаря, аргументированность, стилистическая уместность) с разницей средних показателей в пользу экспериментальных групп на 1,73-2,25 балла по 10-балльной шкале. Индекс мотивационной вовлеченности в изучение речевых дисциплин в экспериментальной выборке вырос с 0,479 до 0,786 (прирост 64,09%), тогда как в контрольной – лишь с 0,482 до 0,514. Обобщение данных позволяет заключить, что интеграция интерактивных технологий обеспечивает комплексное развитие когнитивного, деятельностного и аксиологического компонентов речевой культуры, сокращает разрыв между теорией и практикой и может быть рекомендована для модернизации рабочих программ по журналистике и родственным гуманитарным направлениям. In the context of the rapid digitalization of the media space and the increasing complexity of professional requirements for journalists, the aim of the study was to provide a theoretical justification and an experimental verification of the effectiveness of interactive educational technologies in the formation of journalism students’ speech culture. On the basis of journalism faculties of three humanities universities, a comprehensive pedagogical experiment was conducted during 2019-2023 with the participation of 342 students divided into control and experimental groups; the study employed system-activity and competence-based approaches, standardized tests of language norm proficiency, content analysis of media texts, expert assessments by editors and lecturers, participant observation of speech behavior in interactive classes, as well as methods of mathematical statistics (Student’s t-test, Mann-Whitney U-test, correlation and factor analysis). In the experimental groups, an author’s model was implemented, including case studies, debates, role-playing games, project-based work, podcasting, the flipped classroom, multimedia longreads, and collaborative digital text editing platforms. The results demonstrated a statistically significant increase in the proportion of students with a high level of the normative component of speech culture (from 11,9% to 34,2%) and a decrease in the proportion of those with a low level (from 38,8% to 12,4%) against the background of minimal changes in the control groups; a substantial improvement in communicative and pragmatic skills (logical and coherent speech, lexical richness, argumentation, stylistic appropriateness) was recorded, with an average score difference in favor of the experimental groups of 1,73-2,25 points on a ten-point scale. The motivational engagement index for studying speech-related disciplines in the experimental sample increased from 0,479 to 0,786 (a 64,09% growth), while in the control sample it rose only from 0,482 to 0,514. The synthesized data suggest that the integration of interactive technologies ensures the comprehensive development of cognitive, activity-based, and axiological components of speech culture, narrows the gap between theory and practice, and can be recommended for the modernization of journalism curricula and related humanities programs.
The main objective of the article is to reveal the similar and different features of phytonym lexical units in the same language family, Oghuz group of Turkic languages: Azerbaijani, Turkic, Turkmen and Gagauz languages.Even though the same concept is expressed by similar or identical words in the languages belonging to the same language family, sometimes it can mean completely different meanings like homonyms.Also, with the adoption of Islam, the words of Arabic origin in the Azerbaijani, Turkish, and Turkmen languages formed a majority in the lexical layer of the language, compared to the language of the Gagauz Turks belonging to the Christian faith.Research method and methodology.In the article, the phytonym lexicon units included in the currently working vocabulary of the four languages of the Oghuz group: Azerbaijani, Turkish, Turkmen and Gagauz languages are studied in a comparative plan.Also, rich material related to four languages is compared using statistical, etymological, historicalcomparative, analysis and synthesis methods.Novelty of the article.Previously, units of phytonym lexicon in Turkic languages of the Oghuz group were not studied under a separate heading.This study can serve as a resource for those who study the similarities and differences between related languages at the lexical level, those who study the lexical layer of the Oghuz group of Turkic languages, and those who compile a dictionary related to the phytonym lexicon in Turkic languages in the future.Results.It is possible to see that there are a number of different points in the study of the phytonym lexicon in the Turkic languages of the Oghuz group.It is possible to see these either in the processing of words in different forms, in the feature of homonymy, as well as in the formation of phytonymic units in different forms.Differences in letter and sound changes are observed in words that are similar with minor differences.All this suggests that although the Azerbaijani, Turkic, Turkmen and Gagauz languages, which are part of the Oghuz group of Turkic languages, belong to the same language family, they have many differences in the lexicon of phytonyms.As the Azerbaijani, Turkish, Turkmen and Gagauz languages are included in the Oghuz language family, there are many similar words in their lexical fund.In the literary lexicon of Azerbaijani, Turkish, Turkmen, and Gagauz languages, similar words are sometimes written according to the same orthographic norm, and sometimes there are different spellings, even though the orthographic norm is expected.
BACKGROUND: Emotion dysregulation is a central feature in trauma-associated disorders such as posttraumatic stress disorder (PTSD) and borderline personality disorder (BPD). However, it remains unclear whether emotion dysregulation is a transdiagnostic phenomenon closely linked to childhood trauma, or if disorder-specific alterations in emotion processing exist. Following a multimethodological approach, we aimed to assess and compare the reactivity to and regulation of emotions between patients with BPD and PTSD, as well as healthy controls, and identify associations with childhood trauma. METHODS: A total of 135 women, 43 healthy controls, 43 with BPD and 49 with PTSD, took part in a multimethodological assessment of emotional reactivity and regulation. Self-report measures were used to assess childhood trauma and emotion dysregulation. Additionally, participants performed a classic emotion regulation (ER) paradigm. Subjective emotional valence ratings and neurophysiological responses (P3 and late positive potential, LPP) were measured in response to negative, positive, and neutral pictures (emotional reactivity) and during active regulation vs. passive viewing of negative pictures (ER). RESULTS: Regarding emotional reactivity, during the experimental paradigm both patient groups reported lower emotional valence after viewing positive or neutral pictures compared to healthy controls. Furthermore, P3 amplitudes in response to neutral pictures were reduced in both patient groups and in response to negative pictures, specifically in patients with PTSD. Regarding ER, while both patient groups self-reported significant disturbances in ER, neither valence ratings nor neurophysiological responses assessed during the ER task (P3, LPP) differed from healthy controls. Across groups, childhood trauma was related to decreased emotional valence ratings on neutral and positive pictures and higher self-reported emotion dysregulation. CONCLUSIONS: Patients with BPD and PTSD exhibited a reduced emotional reactivity in response to positive and neutral information. Specifically, patients with PTSD demonstrated hypo-reactivity to neutral and trauma-unrelated negative stimuli, which might be due to altered attentional resource allocation following trauma. Although patients reported using adaptive ER strategies less frequently in daily life, they effectively implemented them when instructed to, highlighting important clinical and theoretical implications.
The future of healthcare delivery across the cancer continuum holds great promise and challenge. U.S. cancer mortality across all cancers combined decreased ~2% annually from 2015 to 2019 thanks to a range of factors including clinical and delivery innovations in cancer prevention, control, treatment, supportive care, and efforts to improve clinical trial access [1]. However, long-standing cancer health disparities remain. Accelerated progress is vital to reduce cancer deaths for all Americans and achieve National Cancer Plan goals [2-4]. Additionally, COVID-19 impacts on cancer are still emerging [5, 6] and the long-term cancer survivor population is growing—increasing sustained surveillance for recurrence, new cancers, late effects, and other long-term health concerns [7]. These and other individual, institutional, and societal trends are shaping cancer care delivery, treatment, and research. Cancer health services research has a role in tracking and understanding how such trends influence health service design, delivery, and outcomes, to inform care approaches, health system decisions, and policy innovation across the cancer continuum. Such trends also beg the question, what measurement and methodological innovations are needed for timely, valid evaluation of their impact on cancer-related health services and outcomes important to patients, caregivers, healthcare professionals, payers, and policy makers? Continued measurement and methodological development only stand to improve scientific quality, reproducibility, and practical impact. Therefore, in this commentary, we briefly summarize 10 trends in cancer care delivery, treatment, and research and explore potential implications for health services research measurement and methods. Our intent is not to comprehensively address all possible opportunities or ideas presented here, but to highlight pressing, foundational needs and promising directions for measurement and methods focused science. Our focus is cancer health services research. However, the challenges and opportunities discussed clearly have broader implications. Rededication to strengthening our research methods and measures is an investment in the foundational T0 basic science [8] of cancer health services research and, therefore, essential to generating and translating future evidence into practice and policy. A universe of trends influences health services at-large at any given moment, however, we highlight 10 trends elevating the necessity of methods and measures research in cancer-focused health services research, including: (1) precision oncology; (2) whole-person perspectives; (3) health technologies (e.g., artificial intelligence (AI), mobile health, telehealth); (4) expanding in-home and community-based services; (5) health system integration and efforts addressing care fragmentation; (6) workforce capacity and evolving roles; (7) population aging; (8) improving safety, quality, value and access while controlling costs and addressing financial toxicity; (9) addressing social drivers of health; and (10) leveraging data oceans with unstructured, semi-structured, and structured elements. Deep discussion of each is beyond our scope, but we discuss several of these trends with examples and then give focused attention to measurement and methodological implications. One trend with significant measurement and methodological implications is the rapid advancement of precision oncology paradigms. Precision paradigms are fundamentally changing the understanding of cancer risk, diagnosis, disease profiling, treatment monitoring, therapeutic development, trial eligibility, and have birthed new health services (e.g., genetic counseling, in-house molecular pathology) [9-11]. Precision approaches highlight potential pitfalls of analyses by organ site (e.g., lung, breast) that lump together variations in genetic or social risks, different genomic signatures, treatments, and implications for prognosis and quality of life (QOL) [12-14]. Population aging and movement toward whole-person health similarly underscore opportunities to assess and model a broader constellation of factors (e.g., multiple chronic conditions, functional status, degrees of caregiver support) and understand the effects of incentivizing wholistic care approaches on cancer-related outcomes [15, 16]. Paralleling rapid clinical advancements is increasing attention on controlling costs, including addressing financial toxicity and financial distress [17, 18]. Cancer care costs increasingly outpace other areas; for example, they comprised 43% of 2020 Medicare Part B spending [19]. Additionally, recent analyses found cancer survivors were nearly 4 times more likely to declare bankruptcy and experienced credit score declines persisting up to nearly 10 years post-diagnosis [20]. Financial distress is associated with higher symptom burden, worse QOL, and lower adherence to recommended care [21-23]. Challenges quantifying costs or balancing cost with access to high-quality care and clinical innovations are certainly not new [24]. However, the scope and duration of cancer care costs at individual, family, and population levels beget opportunities for multilevel measure development, innovative modeling approaches, and data linkages, as well as interventions that integrate financial considerations into goals of care discussions and financial navigation [25-27]. The speed of cancer care innovation is also matched by rapid transformations in the healthcare system landscape across the cancer continuum. For example, in 2017 more oncology physician practices (50%–55%) reported vertical integration with a hospital or health system compared with any other specialty, up from ~20% in 2007 [28, 29]. Trends toward greater health system integration, new affiliation models, expansion of non-traditional players into the care delivery sector, and pervasive care fragmentation underscore opportunities to develop and adopt richer measures of organizational structure, functioning, policies, norms, and coordination across the cancer continuum [30]. Similarly, evolving roles and approaches to care are arising from clinical innovation (e.g., home-based screening, oral anti-cancer agents) paired with patient volumes rapidly outpacing oncology workforce capacity. For example, some care delivery models, state policies, and billing guidelines are enabling Advanced Practice Professionals, community health workers, patient navigators, home care, and other care team members to practice at the top of their license or certification [16]. These trends challenge future research to more precisely assess where and who is delivering care and to advance methods suitable for evaluating contributions of a growing constellation of collaborators and settings to cancer-related outcomes of interest. Additionally, the field has seen increased focus on understanding and addressing adverse social drivers of health, financial hardship, and social risks (e.g., transportation, food, housing instability) and their influence on persistent cancer health disparities [31]. For example, eliminating cancer health disparities was one of eight goals in the 2024 National Cancer Plan [32, 33]. NCI has a long history of supporting efforts to improve cancer health disparity measurement [34] given quantifying heterogeneity in cancer incidence and mortality is part of the Annual Report to the Nation on Cancer. However, efforts to address social risks and drivers of health via the healthcare system—as well as related measures and approaches for tracing impact on cancer outcomes—are still nascent. Collectively, these trends and others noted at the opening of this section underscore numerous opportunities for cancer health services scientists to address persistent and emerging measurement and methodological challenges. We highlight several opportunities for future measurement and methods development or refinement below. We simultaneously encourage the field to identify and pursue numerous others not discussed here. Many trends above may necessitate new measurement paradigms (e.g., whole-person cancer care, measurement-based care). Others underscore the need for dedicated attention toward solving persistent, yet fundamental measurement challenges (e.g., evolving care delivery settings, usual care, organizational characteristics). Given these trends, we discuss five example areas for measurement-focused research attention below. Evidence exists for the benefit of whole-person care models, yet defining components of whole-person cancer care requires conceptual elaboration, refinement, and standardization [35]. Both new measures and novel person-centered methods are essential to designing and optimizing whole-person focused systems of cancer care. In 2024, building from work in primary care, the Integrative Oncology Leadership Collaborative (IOLC) defined whole-person cancer care as an approach that integrates conventional cancer treatments with evidence-based complementary therapies and/or lifestyle interventions, addresses the physical, emotional, social, and spiritual aspects of a person's life, and focuses on what matters most to the patient [36, 37]. The IOLC definition and related minimal-required elements are based on the Two-Circle Model of Whole-Person Care [38], which reframes current disease-focused approaches toward one that is person-centered, relationship-based, and recovery and health-promotion focused. An emphasis on person-centered care, coordination, continuity and integration, and relationships are distinguishing characteristics of the whole-person paradigm and are conceptualized as features most likely to improve population health, access, quality, and lower costs. The Two-Circle framework also highlights roles, services, and workforce changes needed to implement, scale up, and sustain this type of care. New payment models are also important to support and incentivize a transition to whole-person care. Many health services measurement and methodological approaches developed or operationalized around a single disease, organ system, specific health care setting, or payer will continue to be useful in evaluating models of whole-person cancer care (e.g., cancer registries, Consumer Assessment of Healthcare Providers & Systems [CAHPS]) [39-41]. However, person-centered measures of unmet needs, experiences of care involving larger care teams, well-being (physical, emotional, social), care costs, and medical financial hardship will require further conceptual, lexical, and methodologic development in the context of whole-person care [42]. Ensuring such measures are accessible and meaningful for all patients, and interpretable as predictors and moderators of whole-person health outcomes will require mixed methods studies that go beyond traditional psychometric approaches to establish validity and interpretation [43]. Measurement of whole-person outcomes also requires accommodating, sometimes simultaneously, for within-person and group-level change, and methods able to address differences between individuals on a collection of measures or scale dimensions (e.g., almost matching exactly methods) [44]. The NIH National Center for Complementary and Integrative Health's 2021 Workshop on Methodological Approaches for Whole Person Research discussed several such measurement and methodological opportunities [45]. Measurement-based care (MBC) is an emerging approach in chronic disease management, including cancer care [46], generally defined as “systematic evaluation of patient symptoms before or during an encounter to inform” [47](p324) care-related decisions. Patient-reported outcomes (PROs) form MBC's foundation, providing critical tools for assessing targeted needs for distinct populations (e.g., older adults, adolescents), tumor and treatment types, and care phase [48]. Well-validated instruments essential for MBC in oncology exist (e.g., needs assessment, symptoms, functional status, social risks) [49-51]. However, some domains remain underdeveloped, including measurement of treatment burden, patient engagement, and care experiences. Both existing and newly developed measures also require adaptation and validation to meet accessibility needs of all patients, including groups understudied in measure development research such as older adults and people with differing degrees of English language proficiency. Additionally, integrating these measures into feasible, efficacious MBC interventions and coupling them with evidence-based decision support necessary to prioritize and comprehensively address the constellation of needs identified, requires further development. Alternative settings of care beyond traditional inpatient-outpatient distinctions are also rapidly arising, including: telehealth, remote patient monitoring, home-based care (e.g., hospital-in-the-home, self-management support), distributed clinical trials, and consumer-oriented platforms (e.g., Amazon Care, CVS MinuteClinic). These settings offer new opportunities for interdisciplinary collaboration, improved efficiency, and access. However, the field lacks screening measures to match these settings to patient needs and resources, risk stratify, and predict clinical complications. Also needed are bespoke measures demonstrating solid measurement properties in these settings for care quality, safety, clinical outcomes, budget impact, costs, value, and experiences of patients, caregivers, and staff [52-54]. Measuring strategies and contextual factors contributing to the adoption and sustainment of delivery models employing alternative care settings are also important for dissemination and adaptation [54, 55]. 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About the Linguistic Analysis of Text Summary The article considers the problem of linguistic analysis of text. There are two directions in the study of text linguistics. One of the directions studies the relationship between the text system and the language system in order to verify and clarify general conclusions concerning the language system. The other direction aims to study the features of the text itself as a spe¬cial system. A linguistic norm has the force of law and is characterized by certain features. The norm expresses the necessary connections found in the text, without which its functioning is impossible. The most important feature of a linguistic norm as a law is the expression of general connections. This feature receives a clarifying characteristic in linguistics: language norm − speech norm − text norm. The most promising is the information-structural theory of the text-system. This theory is based on the definition of language in all its manifestations and abstractions as the most important means of communication. Such factors as content and form, structure and system interact in the text. Keywords: text, linguistic norm, language means, communication, information, methods of analysis, content, form, structure, system
Abstract: The Hebrew language and its rapid development played a crucial role in modern Jewish history. However, scholarship on Modern Hebrew has not sufficiently explained how its abstract status as a national language was translated into the practical promotion of a Modern Hebrew–speaking community. The path of Hebrew and its advocates was neither simple nor serene and was accompanied by a lively public discussion across the multilingual Jewish press. By examining key press debates that occurred between 1875 and the outbreak of World War I, this article traces the formation of new linguistic norms. It shows how conventions concerning the national status of Hebrew, its prospect as a modern language, and its potential to serve as the basis of a new Jewish society were crystallized and laid the foundations that enabled it to become, eventually, a modern national language.
This entry presents a comprehensive overview of the computational study of Old English that surveys the evolution from early digital corpora to recent artificial intelligence applications. Six interconnected domains are examined: textual resources (including the Helsinki Corpus, the Dictionary of Old English Corpus, and the York-Toronto-Helsinki Parsed Corpus), lexicographical resources (analysing approaches from Bosworth–Toller to the Dictionary of Old English), corpus lemmatisation (covering both prose and poetic texts), treebanks (particularly Universal Dependencies frameworks), and artificial intelligence applications. The paper shows that computational methodologies have transformed Old English studies because they facilitate large-scale analyses of morphology, syntax, and semantics previously impossible through traditional philological methods. Recent innovations are highlighted, including the development of lexical databases like Nerthusv5, dependency parsing methods, and the application of transformer models and NLP libraries to historical language processing. In spite of these remarkable advances, problems persist, including limited corpus size, orthographic inconsistency, and methodological difficulties in applying modern computational techniques to historical languages. The conclusion is reached that the future of computational Old English studies lies in the integration of AI capabilities with traditional philological expertise, an approach that enhances traditional scholarship and opens new avenues for understanding Anglo-Saxon language and culture.
The article is devoted to the exploration of feminist discourse within the realm of sports journalism, analyzing how language and media representation shape and challenge gender norms in the coverage of athletes.The work examines the linguistic and pragmatic strategies used in sports journalism to reinforce or dismantle gender stereotypes, with an emphasis on promoting equality and inclusivity.Particular attention is paid to the combination of feminist theory and media communication, as well as the influence of lexical choice, metaphors, syntactic structures and framing techniques on the representation of female athletes and non-binary individuals in sport.The relevance of this topic is due to the importance of feminist discourse as a special type of communication aimed at eliminating patriarchal language norms that emphasise traditional gender roles rather than sports performance in media.It highlights how language in sports journalism serves as a powerful tool for shaping gender perceptions through the use of images and narrative structures that help eliminate bias.The article examines how these linguistic strategies have a direct impact on the development of the gender equality movement in the sports media sphere.The scientific novelty of the study lies in a comprehensive analysis of feminist discursive strategies common to sports journalism, a field traditionally dominated by masculine narratives.Examining real-life examples from major media sources and international sporting events, the paper reveals both problematic practices and progressive changes in the industry.It also contributes to the broader discourse on gender and media suggesting effective linguistic strategies such as neutral terminology, active constructions and inclusive framing, that can transform sports journalism into a more equitable media space.The study establishes a new framework for feminist linguistic activism in sports media that contributes to the deconstruction of gender stereotypes and the formation of narratives that promote equality and visibility of underrepresented gender identities.
Dependency parsing is a fundamental task in natural language processing that involves identifying the grammatical relationships between words in a sentence. One promising approach for performing this task in languages lacking annotated treebanks is treebank translation, which utilizes word alignments to map dependencies from a source treebank to the corresponding target translation. However, due to language differences and the limitations of word alignment tools, this method would inevitably generate noise during mapping. To reduce the effect of noise, we first exploit MetaNet to compute quality scores for each dependency and identify low-score ones as noise. MetaNet is a fake teacher that learns to score homework (dependencies) by comparing answers from the top student (strong parser) and the regular student (weak parser) without knowing the correct answer (gold-standard). With the scoring capability of MetaNet, we design an iterative algorithm to boost the target treebank quality, which trains with high-quality dependencies and relabels the low-quality dependencies. Our method achieves better results than the originally translated treebanks and shows highly competitive performances with prior methods on the Universal Dependency Treebanks v2.2. We also provide detailed analysis and discussions.
Acceptability judgments are one of the major tools for (psycho)linguists to assess speakers’ preferences for specific utterances in a given language, shedding light on the grammar of the language under study. However, it is well known that factors that are not related to grammaticality, such as frequency of exposure, cognitive constraints, and others, can influence the perceived acceptability of an utterance. We will use the system of wh-interrogatives in French as an example to study the impact of linguistic norms on what is considered “good” French. In three experiments, we show that adult L1 French speakers have internalized the dichotomy between variants that are considered “good French”, according to the norms, and those that are suited to more informal daily life situations. Speakers can express these differences when given the appropriate tools, but not with a unique general acceptability scale. In line with previous work, we argue that acceptability judgments are a useful task, but that they need to be refined to account for sociolinguistic factors that constrain speakers’ assessments (i.e., linguistic norms, but also speaker group and formality of the context of interaction).
We address the challenge of syntactic parsing for Urdu, a morphologically rich language, and present state-of-the-art results for both constituency and dependency parsing. This paper offers four major contributions: 1) the conversion of the CLE-UTB phrase structure treebank into a dependency treebank by developing language-specific head-word and phrase-to-dependency label mapping rules; 2) a novel sequence labeling scheme that transforms the parsing task into a unified representation; 3) the training of contextualized word representations on a large 220 million tokens Urdu corpus collected from the web; and 4) development of parsing framework using two learning paradigms, single-task and multi-task learning. Several post-processing rules are applied to improve the quality of the automatically converted dependency structure treebank. The proposed sequence labeling scheme enables the use of a shared architecture that learns the syntactic structures from both grammatical structures simultaneously and hence improves generalization. Experiments show that the multi-task learning setup significantly enhances parsing performance, achieving an F1 score of 91.39 for constituency parsing (an improvement of 3.29 points) and a labeled attachment score of 85.69 for dependency parsing (an improvement of 1.49 points). These results demonstrate that learning cross-task representations provides measurable benefits and advances the state of syntactic parsing for Urdu.
This article explores the nature, functions, and significance of discursive formulas in academic writing, with a focus on comparing their usage in English and Uzbek academic articles. The study highlights the similarities and differences shaped by linguistic norms and rhetorical traditions.
Abstract Cartographic maps aim to identify the order of generation and understand, by explaining in terms of syntactic strategies, the derived orders. In this work, we focus on the order of core verbal arguments and how the PP-NP order is derived from a basic NP-PP order. We test three models of syntactic operations (criterial model, meaningless movement, and external merge) and their predictions using quantitative and computational tools. Specifically, we implement two studies across nineteen treebanks in sixteen languages (four treebanks for Italian and Hebrew in Study 1; fifteen parallel treebanks in Study 2) to test the predictions in terms of locality for the different models. Our results show that the criterial model better predicts the data.
The formation of communicative skills in foreign students is impossible without mastering language norms. The study of Russian verbs of motion, including their lexical and grammatical features, is among the most difficult challenges for Iranian audience. Most often, when studying Russian verbs of motion, students get acquainted with the direct and basic meanings of the verbs. The practice of teaching Russian as a foreign language shows that Iranian students often have no idea about figurative meanings of verbs of motion. Moreover, the ability of verbs to combine with different affixes and acquire new lexical and grammatical characteristics complicates the process of mastering their figurative meanings. The fact that verbs of motion are frequently used not only in everyday life but also in business communication makes it necessary to teach figurative meanings in audiences studying Russian as a foreign language. This research paper analyzes the methods of translating figurative meanings of the verbs of motion ‘прийти – приходить’ into Persian. The purpose of this article is to study the figurative meanings of these verbs in Persian as well as the linguistic means by which these meanings are conveyed.
The purpose of this study is to investigate what norms are prominent around the drag culture as well as how masculinity and femininity is represented in the fourteenth season of RuPaul’s Drag Race (RPDR). This has been done with a multimodal critical discourse analysis (MCDA) where I have analysed the lexical choices as well as the visual attributes that contribute to the norms. I have applied Connells (2005) masculinity theory, Skeggs (2000) femininity theory and Duggans (2003) theory about homonormativity. The analysis has shown how RuPaul’s Drag Race represents a norm that drag queens are supposed to desire men rather than the norm of being a homosexual man, even though the norm of being a homosexual man still occurs. Furthermore the analysis has shown that the series reproduces a norm that one should strive to be thin as well as being young. Being old is something that should be hidden. In reference to how masculinity is depicted, the study has shown how the hegemonic masculinity is the homosexual one and how masculinity is done differently in the context of RuPaul’s Drag Race compared to life outside of the series. Lastly the study’s analysis has shown how the normative femininity is created in opposition to the deviant femininity by the drag queens appearance and behaviours.
Music- and distraction-induced pain reduction have been investigated extensively, yet the main mechanism underlying music-induced analgesia remains unknown. In this study, to assess whether music-induced analgesia primarily operates through cognitive modulation, we used the cold pressor task and objectively compared the pain tolerances of participants in a four-group between-subjects design: a music group that listened to a music piece in the absence of any tasks, a music-and-attention-to-music group that listened to the same piece while also rating the arousal levels in the music, a music-and-attention-to-pain group that rated their pain levels while listening to the same piece, and a silence group as control. The group passively exposed to music playback did not show significantly higher pain tolerance compared to the silence group. However, pain tolerances in the music group negatively correlated with participants' self-reported arousal ratings of the music at the end of the experiment. The groups that engaged in an active task - whether evaluating the arousal levels in the music or reporting their experienced pain levels - demonstrated similarly higher pain tolerances compared to the silence group. These findings suggest that engaging in a task, regardless of whether it involves exteroceptive or interoceptive attention, can enhance pain tolerance.
The author’s aim is to define the so-called linguistic norm of Middle Armenian using specially developed criteria and linguistic models, and to apply this framework to the study of Middle Armenian. This research presents a methodological and preliminary attempt to address this issue. The linguistic norm is considered essential for the Middle Armenian period, as this is the era in which various forms of Armenian emerge and gain broad usage. A linguistic norm represents the status of a language during a certain time – whether it is stable and systematic or unstable and disorganized. For this reason, the author proposes the following necessary criteria for defining the linguistic norm in Middle Armenian: a) absolute and relative, b) general (societal) and individual (private), c) written (literary) and oral (colloquial), d) comprehensive and segmented in time. The author concludes that it is impossible to define a single unified linguistic norm for the entire Middle Armenian period as one coherent system of rules. One must take into account its diversity and irregularities across centuries. Thus, it may be more appropriate to speak of a mixed type of linguistic norm - dominated by variations and inconsistencies - or to distinguish between multiple linguistic norms that together encompass all linguistic areas as a whole. The author also suggests adopting the regional linguistic feature as a criterion for the linguistic norm of Middle Armenian, which would clarify the localization of dialectal features according to specific regions.
Abstract. The article deals with the peculiarities of teaching translation of specialized texts of non-linguistic specialties students. When teaching a foreign language, it is necessary to develop translation skills, as well as pay special attention to the tools used for its implementation. The author emphasizes that there are many lexical and grammatical transformations that are used to correctly construct specialized texts from the point of view of grammar and vocabulary. Some of the most common in the translation of specialized texts in-clude antonymic translation and compensation. The necessity of using antonymic transformation is caused by the necessity of precisely convey the semantic content of the original statement. The presence of close interrelation in speech and mutual influence can some-times change the meaning of the translated text. This is stipulated by the peculiarities of the words meaning in the context of using its direct, rather than figurative equivalence. Another widely used technique in specialized texts translation of various subjects is compensation. This translation technique is contextual, i.e. its use in the translation process serves to fully convey the meaning of the original. The success of its application also depends on understanding the emotional coloring of the state-ment itself, the character and features of the speaker’s speech, the initial situation and the specifics of the translation topic. Explication is also used in teaching translation of specialized texts and is a process of explaining and in-terpreting a text, which includes the analysis of lexical, grammatical and stylistic features. Explication is an important tool in teaching translation of specialized texts. It helps students develop a deep understanding of the text, improve their analytical and critical thinking skills, and take into account cultural features in the process of translation. The author comes to the conclusion that antonymic translation, explication and compensation contribute to achieving maximum equivalence and adequacy of translation, and the translated text reflects all the stylistic features of the original, while strictly following the language norms.
The overall goal of this article is to contrast the different theorisations of norms in linguistics. Starting from the branches of structural linguistics, the article shows how linguistic norms are conceived in anthropological linguistics. Whereas the former separates linguistic usage from the speakers and tries to describe and analyse the linguistic structures which form different linguistic norms, the fields of anthropological linguistics as well as qualitative sociolinguistics and pragmatics focus on the contextually bound social functions and ideological implementations of the linguist signs that linguistic norms consist of. This way, linguistic norms can be understood more broadly as norms of conceiving and structuring social behaviour of which linguistic behaviour forms an integral part. Consequently, the social functionality of norms and the signs they consist of are theorised in this article. In order to demonstrate their social underpining, the example « J’aime right ton accent » in Acadian French will be analysed in more detail.
Information on the relationship between facial thermal responses and emotional state is valuable for sensing emotion. Yet, previous research has typically relied on linear methods of analysis based on regions of interest (ROIs), which may overlook nonlinear pixel-wise information across the face. To address this limitation, we investigated the use of machine learning (ML) for pixel-level analysis of facial thermal images to estimate dynamic emotional arousal ratings. We collected facial thermal data from 20 participants who viewed five emotion-eliciting films and assessed their dynamic emotional self-reports. Our ML models, including random forest regression, support vector regression, ResNet-18, and ResNet-34, consistently demonstrated superior estimation performance compared to traditional simple or multiple linear regression models for the ROIs. To interpret the nonlinear relationships between facial temperature changes and arousal, saliency maps and integrated gradients were used for the ResNet-34 model. The results show nonlinear associations of arousal ratings in nose = tip, forehead, and cheek temperature changes. These findings imply that ML-based analysis of facial thermal images can estimate emotional arousal more effectively, pointing to potential applications of non-invasive emotion sensing for mental health, education, and human-computer interaction.
The article notes that one of the key tasks of higher education in the context of modern reforms is to improve the professionalism and qualifications of future specialists. This requires the introduction of innovative approaches to the training of a new generation of specialists based on clear conceptual principles. The entire system of training in higher education institutions should be structured and logically organized, with hierarchical elements. The content of education should include all aspects necessary for their future activities, taking into account changes in professional requirements, and should be aimed at stimulating creativity, originality and the ability to solve problems in a nonstandard way. Students should learn to move from reproductive knowledge acquisition to constructive activity, which allows them not only to learn but also to apply it in practice. The article describes theoretical and practical aspects of the formation of students' lexicological competence, which is an integral part of the future teacher's professional training. Particular attention is focused on such aspects as the content and scope of lexicological competence, the use of a linguodidactic approach in its formation, especially in the process of studying lexical phenomena, taking into account their specificity, is substantiated. The article presents indicative tasks and exercises aimed at effective learning of lexical norms by students. This practical instrument allows optimizing the learning process and achieving high-quality results in the formation of language competencies and overcoming anomalies in written and speaking communication. These methods help to improve the effectiveness of students' mastery of language phenomena at the lexical level and the formation of the necessary professional skills. It is noted that the formation of the lexicological competence of a modern teacher takes place through a consistent, phased and purposeful process of mastering professionally relevant knowledge, skills and abilities.
Understanding how performance expression affects perceived emotion requires separating the effects of notated music from its interpretation by performers. Previous studies suggest that compositional cues (e.g., the pitches of a melody) primarily convey valence (negative–positive emotional quality), whereas performance cues (e.g., performance timing, intensity) convey arousal (low–high emotional intensity). However, these conclusions largely follow from simple single-line stimuli that lack the complexity of real-world music. To explore compositional and performance contributions to emotion in more complex works, we conducted experiments comparing participants’ ( N = 120) valence and arousal ratings of 48 recorded excerpts from a Grammy-winning pianist against parallel deadpan versions lacking emotionally expressive aspects. By comparing differences in ratings of stimuli presented in expressive and deadpan conditions, we corroborate past findings highlighting performance contributions to perceived emotion, while also providing novel insight into the relative importance of analyzed cues. Our findings reveal that removing expressive aspects (i.e., the deadpan condition) significantly affects arousal ratings of 21 excerpts, but valence ratings of only 4. Additionally, we highlight how cues differ in importance between expressive and deadpan conditions through a novel analytical approach employing elastic nets. Our analyses shed new light on how performance expression affects emotions communicated across complex musical works with different levels of compositional cues.
This article examines the processes of linguistic normalization in Ukrainian during the period of Ukrainization in the 1920s and their reflection in the Ukrainian-language press of Kuban (RSFSR). The analysis focuses on the use of noun standards in issue No. 4–5 of the pedagogical journal "Novym shlyakhom" (1928), published in Krasnodar between 1927 and 1930 as the organ of the Central Council of National Minorities of the People’s Commissariat of Education of the RSFSR. The study demonstrates that the editorial board was well-informed about the discussions on Ukrainian orthographic norms that were taking place in the Ukrainian SSR under the supervision of the Orthographic Commission of the People’s Commissariat of Education of the Ukrainian SSR. Special attention is paid to grammatical markers in the sections "Gender of Nouns", "Genitive Singular of Nouns", "Locative Singular of Nouns", and "Genitive Plural of Nouns". The findings show that noun inflection largely conformed to the standards codified in the "Ukrainian Orthography" of 1928. Interference in noun inflection proved to be minimal, while the expanded application of certain grammatical norms indicates a conscious strategy of asserting Ukrainian linguistic identity in the predominantly Russian-speaking environment of Kuban. The article also identifies dialectal features associated with the Kuban vernacular and considers the reasons for their occurrence in the pedagogical discourse. In addition, biographical traces of some contributors to the journal are explored. The study concludes that communication between Ukrainization activists in the RSFSR and their colleagues in the Ukrainian SSR was limited. Promising directions for further research include: word-formation analysis of neologisms and historicisms of the Ukrainization period in Kuban; orthographic analysis of texts; conceptual and semantic study of the lexical corpus; and sociolinguistic analysis of the journal’s discourse.
Introduction. This article analyses media practices of euphemisation in diplomatic communications during Ukraine's War of Independence. The relevance of this research stems from the transformation of diplomatic and media communication in the context of full-scale war, when language becomes not only a tool for informing, but also a space for competing interpretations, legitimising decisions and shaping public opinion, where euphemisation acts as a means of preserving international solidarity, softening tragic realities and legitimising complex political decisions. Methods. The study uses discourse analysis of diplomatic speeches and media news reports, content analysis of quotations and their media presentation, comparative analysis of media texts and diplomatic sources, generalisation for the processing of theoretical sources, the method of contextual analysis to identify euphemisms and the process of euphemisation, as well as the method of classification to structure the most common techniques of euphemisation in diplomatic messages. Results and discussion. It has been established that the euphemisation of diplomatic messages during the War for Ukraine's Independence is a systematic linguistic-pragmatic strategy that functions at the intersection of diplomatic and media discourses and significantly influences the formation of public perceptions of the war. An analysis of the corpus of diplomatic statements, speeches by the President of Ukraine, Ukrainian diplomats and their media broadcasts revealed the dominance of lexical, syntactic and pragmatic euphemisation techniques aimed at softening, abstracting and neutralising direct references to war, violence and political responsibility. It has been found that diplomatic discourse consistently uses nominalisation, impersonal constructions and generalised formulas to reduce agency and avoid directly naming the aggressor, which is in line with the norms of institutional diplomatic communication and strategies of deliberate ambivalence. Ukrainian media, retransmitting these messages, mostly reproduce euphemistic formulas without change, thereby institutionalising them as a habitual model of speaking about war. Two levels of euphemisation have been identified: primary - in diplomatic speech, and secondary - in media representation, where euphemisms are reinforced through headlines, quotations and editorial interpretations.
The concept of Global Englishes (GE) redefines English as a pluralistic and dynamic entity shaped by sociocultural contexts worldwide, challenging traditional native-speaker norms. This study explores the historical, sociopolitical, and linguistic dimensions of GE, focusing on its implications for English language education and policy in Thailand. Thai English, a localized variety influenced by Thai linguistic and cultural norms, exemplifies how non-native speakers creatively adapt English to suit local communicative needs. Key linguistic features of Thai English, including distinct pronunciation patterns, lexical innovations, grammatical adaptations, and discourse strategies, reflect the intersection of global and local influences. The study critiques Thailand’s traditional English language teaching (ELT) models, which often privilege Standard English over localized varieties, thereby marginalizing linguistic diversity and limiting students’ communicative competence in global contexts. This paper advocates for integrating diverse English varieties into curricula, enhancing teacher training programs to include GE pedagogy, and promoting multilingualism through inclusive language policies. Emphasizing linguistic diversity and intercultural competence, the study also underscores the need for public awareness campaigns and sustained research to transform societal attitudes and institutional practices. By embracing Global Englishes, Thailand can align its language education policies with the realities of global communication, empowering learners to navigate multicultural contexts confidently. Such an approach contributes to social equity, intercultural understanding, and the development of a more inclusive and globally relevant educational framework.
本研究通过实地调查，广泛收集了净月潭国家森林公园中的语言景观，采用定量分析法进行研究。通过对采集到的语料从语码种类、优势语码和语码标牌类型三个方面进行分析，研究发现，景区内语言景观具有综合性、多模态、双/多语性的主要特征；在语码种类方面，汉语占据主导地位，英语作为强势外语次之，语言模式以双语模式为主；从能见性和凸显性两个方面分析，汉语均为第一优势语码；按功能类型划分，说明介绍标识数量最多，服务设施标识次之，且每种功能类型的标牌都以双语模式为主。然而，景区中语言景观仍存在不少语言文字运用失范和语言标牌信息量不对等等问题。因此，相关部门需要加强对净月潭国家森林公园语言景观的规范建设与监督管理，必要时出台相应的法律法规，以确保语言景观的有效性和规范性。In this study, language landscapes in Jingyuetan National Forest Park are extensively collected through field surveys and studied by quantitative analysis method. It is found that, based on the analysis of the collected corpus in terms of three aspects: code type, dominant code and code sign type, the linguistic landscape in the scenic spot is featured by comprehensive, multimodal and bilingual/multilingual characteristics. In terms of code type, Chinese takes the dominant position, and English, as a powerful foreign language, ranks second. The language mode is mainly bilingual. Analyzed from the two aspects of visibility and salience, Chinese is the primary advantageous code. Divided by functional types, the number of signs for explanation and introduction is the largest, followed by those for service facilities. Moreover, signs of each functional type are mainly in the bilingual mode. However, there are still many problems in the linguistic landscape of the scenic spot, such as linguistic norm violations and informational asymmetry in code signs. Therefore, relevant departments need to strengthen the standardized construction, supervision and management of the linguistic landscapes in Jingyuetan National Forest Park and introduce relevant laws and regulations when necessary to ensure the effectiveness and standardization of the linguistic landscape.
Abstract Sentence length, defined by the number of words contained in a sentence, has always been of great concern in linguistic research. Many studies have been conducted on the distribution of sentence length in specific languages. To further explore the characteristics and patterns of sentence length and their relationship with dependency distance in Spanish, we use the SUD syntactic treebank and conduct a quantitative analysis within the theoretical framework of dependency grammar. It is found that the sentence length distribution of Spanish follows a positive negative binomial model, and there is no significant difference in sentence length distribution among different mean dependency distances (MDDs), but the distribution of the number of sentences in different sentence length intervals follows a normal distribution. In Spanish, sentence length and MDD interact with each other – the longer the sentence is, the greater the MDD is, and vice versa – which is consistent with previous research findings. Also, as sentence length increases in Spanish, short-distance dependencies decrease, but remain within a certain range of fluctuations, which confirms once again that language is a complex and self-adaptive system driven by humans.
The research work examines the syntactic and stylistic features of the language of the press, one of the topics studied in the 30th anniversary of the country's independence at a later stage of syntax in Kazakh linguistics. The article examines the syntax of the Kazakh language of printing; genre classification of the Kazakh language of printing; lexical and grammatical features of the Kazakh language of printing; the function of the syntax of the Kazakh language of printing in the formation of literary norms; Issues such as the definition of syntactic features of newspaper article titles have been consistently considered by materials from the city newspaper “Turkestan”. The works of scientists are devoted to the issues of studying the language of mass media texts, their structural and genre features, discursive, stylistic nature. Both foreign and Kazakh scientists make a great contribution to such research. A number of studies have been conducted in the field of studying individual genres of mass media, the diversity of media cultures, as well as media cultures at various linguistic levels, including syntactic ones. However, so far, a sentence or phrase has not been considered in a comparative aspect based on press materials. The relevance of the topic lies in a comprehensive study of the linguistic features of mass communication, including the scientific direction – a systematic and multidimensional analysis of newspaper texts from the point of view of the emergence and development of media linguistics. In this research paper, one of the directions of studying media texts is, in particular, a comprehensive analysis of the syntactic features of press texts from a linguistic point of view.
This dissertation examines the multifaceted role of pitch by focusing on two central issues. First, it investigates whether lexical tones in Standard Chinese exhibit affective iconicity—that is, to what extent their pitch characteristics (e.g., height, range, slope, and contour direction) systematically aid to signal human emotional expression (e.g., arousal and valence). Notably, while arousal appears to be driven by inherent physiological responses, valence is more influenced by lexical meaning and cultural conventions. Analyses of bi-syllabic and monosyllabic words reveal that higher pitch, wider pitch range, and steeper pitch slopes are linked to higher arousal, whereas lower pitch and falling contours are associated with negative valence. In addition, monosyllabic tonemes more strongly predict emotional arousal ratings than consonants, and emotional valence ratings than vowels. Furthermore, lexical tones show adaptive significance for both arousal and valence, suggesting a potential mechanism of affective iconicity. <br> Second, the dissertation explores the developmental hemispheric lateralization of pitch processing in infants learning different languages. Using functional near-infrared spectroscopy, cross-linguistic comparisons between Dutch (a stress-accent language) and Japanese (a pitch-accent language) infants reveal distinct lateralization patterns. Japanese infants, whose language uses pitch to signal lexical contrasts, exhibit early left-hemispheric specialization for speech stimuli, while Dutch infants exhibit a bilateral response. Together, these studies suggest that pitch perception in language and emotion is shaped by an interplay between the perceptual properties of pitch and linguistic, experiential, and contextual influences.
Although aerobic exercise modulates self-experienced pain, its impact on empathy for pain remains unclear. Moreover, whether exergaming, which combines exercise with interactive gaming, influences empathy-related neural responses is unknown. The present study investigated the effects of exergaming on the neural mechanisms underlying empathy for pain, comparing them with those of conventional aerobic exercise (cycling) and a non-active control condition. A total of ninety-one participants were randomly assigned to one of three conditions: exergaming (Nintendo Fitness Ring Adventure), moderate intensity cycling, or rest. After a 30-min intervention, participants completed a pain judgement task while event-related potentials (ERP) were recorded. Behavioral outcomes (reaction time, accuracy, pain intensity, and emotional valence ratings) and ERP components (N1, P2, N2, P3, LPP) were analyzed. Results revealed that both exergaming and cycling enhanced emotional valence ratings for painful images relative to the control condition. ERP analyses demonstrate that exergaming significantly amplified late-stage components (P3 and LPP) in response to painful stimuli, indicating enhanced cognitive appraisal processes associated with empathy for pain, while early components (N1, P2, N2) remain unaffected across conditions. These findings suggest that exergaming, through its combination of multisensory and cognitive engagement, uniquely enhances cognitive empathy for pain.
Introduction This study investigates how neurotype influences the emotional appraisal of words. Methods A total of 131 Spanish-speaking adults in Chile (63 autistic and 68 neurotypical) rated on a 7-point Likert scale 238 Spanish nouns across six affective dimensions: (a) valence, (b) arousal, (c) subjective frequency, (d) association with depression, (e) association with anxiety, and (f) association with anger. Descriptive statistics and Principal Component Analysis were used to identify differences in lexical-affective ratings. Results The results revealed consistent group differences in the emotional interpretation of words. Autistic participants tended to assign higher ratings to emotionally intense, concrete, and interoceptively salient terms, particularly those linked to bodily sensations, anxiety, or arousal. Words such as inquietud ( uneasiness ), ducha ( shower ), and ansia ( craving ) were rated as systematically more emotionally charged by autistic participants. In contrast, neurotypical participants favored abstract, socially embedded terms like admiración ( admiration ), soledad ( loneliness ), and decepción ( disappointment ), which rely more heavily on symbolic inference and social scripts. These differences were especially marked in the anxiety and arousal dimensions. Modeling results further confirmed that neurotype predicted systematic variation in ratings across all dimensions, suggesting distinct cognitive-emotional frameworks. Discussion The findings support the hypothesis that autistic and neurotypical individuals construct emotional meaning through different experiential systems: one grounded in interoception and perceptual salience, and the other guided by social abstraction. These insights offer implications for inclusive pedagogy, clinical communication, and the design of affective tools in education and therapy. Recognizing neurotype-specific emotional semantics may help reduce miscommunication and foster more adaptive and respectful forms of interaction across neurodivergent and neurotypical populations.
The Reading the Mind in the Eyes Test, Revised (RMET-R) is a widely used measure that purports to assess theory of mind (ToM). However, the psychometric properties of the RMET-R have been called into question. To examine a wider array of the RMET-R's psychometric properties, as compared to prior studies, we recruited undergraduate students ( N = 640; 65.31 % women; M age = 20.33; SD = 4.30) from three public universities. Participants completed the RMET-R, a novel word choice familiarity task, a novel task rating each response option's description of the picture, along with emotional valence and arousal, and two self-report cognitive empathy measures. Results indicated a small positive correlation with one self-report measure of cognitive empathy, and acceptable internal consistency. Performance was related to prior familiarity of words used on the test, and a quarter of the trials had a foil word rated similarly as the target word in describing picture. Item-level analysis found that valence ratings correlated significantly with accuracy, even on the least accurate items. Results corroborate and expand published concerns about the RMET-R's psychometric properties. We propose changes to the measure, including updated stimuli and structural improvements.
INTRODUCTION: The Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) and the Collum-Caput (Col-Cap) concept are tools for clinically assessing cervical dystonia severity. However, the accuracy of human ratings using these scales has not been systematically evaluated due to the lack of objective reference measurements. This study aims to assess and compare the accuracy of human TWSTRS and Col-Cap ratings to evaluate their robustness for clinical and research applications. METHODS: One hundred pictures of 26 avatars mimicking cervical dystonia were created using the Rocketbox Avatar library. Forty-one movement disorder specialists rated the head and neck positioning of the avatars using either TWSTRS or Col-Cap. Movements were defined around two rotational levels (head, neck) in three rotational axes (pitch, yaw, roll). RESULTS: Ratings of angular deviations showed a mean absolute error of 5.8° (SD = 7.0). Rating accuracy was primarily influenced by the magnitude of angular deviation, with larger angles leading to greater estimation errors. Direct comparison of the rating scales revealed a higher accuracy through Col-Cap ratings (71 % vs. 63 % for TWSTRS). Years of clinical experience did not significantly affect rating accuracy. CONCLUSIONS: Both rating systems (TWSTRS and Col-Cap) show moderate accuracy in assessing head and neck positioning from computer-generated avatars, with Col-Cap showing slightly higher overall accuracy but struggling with precise differentiation between head and neck movements. These findings underscore the limitations of current clinical rating scales and highlight the need for more objective, reliable tools to effectively assess cervical dystonia.
This article aims to present a study during which the usage of 94 adjectives was analyzed to identify the adjectives of atypical usage. In this research, atypical adjectives are those that differ from other adjectives in terms of their grammatical and lexical-semantic features. The adjectives were selected from the Lexical Database of Lithuanian Language Usage and analyzed using the Pedagogic Corpus of Lithuanian. In total, 12 relative and 82 qualitative adjectives were examined. The research is based on the principles of lexical grammar, which posits that words with distinct grammatical features tend to also exhibit different lexical-semantic features.The study identified 2 (16.67%) relative adjectives with atypical usage. They are relatively frequently used predicatively (e.g., paskutinis ‚last‘, vidutinis ‚average‘) and possess distinctive lexical semantic features (for example, the adjective paskutinis ‘last’ semantically resembles ordinal numerals). The analysis identified 21 (26%) qualitative adjectives with atypical usage. They were identified, first of all, according to their syntactic functions: some are relatively often used attributively (e.g., bendras ‚common‘, didis ‚great‘, didžiulis ‚huge‘, kultūringas ‚cultured‘), while others are relatively often used predicatively (e.g., aiškus ‚clear‘). These adjectives also exhibit distinctive lexical-semantic features (e.g., kultūringas can also be considered a relative adjective). Qualitative adjectives of atypical usage were also identified based on their connection abilities and gradation. Some of them do not combine with adverbs of measure/degree and cannot be graded (e.g., specialus ‚special‘); some, when used attributively in the positive degree, are relatively often used with words indicating time and place (e.g., garsus ‚famous‘, populiarus ‚popular‘, vienintelis ‚the only one‘); others are relatively often used with the dative case indicating purpose or suitability (e.g., naudingas ‚useful‘, reikalingas ‚necessary‘); some are relatively frequently used with the instrumental case (e.g., garsus ‚famous‘, ypatingas ‚special‘); others can be used with the genitive case (e.g., gausus ‚abundant‘, pilnas ‚full‘, vertas ‚worth‘); some can be used with the prepositional phrase with the preposition į ‘to’ (e.g., panašus ‘similar’); and others are used with a subordinate clause when not in the neuter gender (e.g., tikras ‚sure‘). These adjectives also tend to have distinctive lexical-semantic features (e.g., the adjective tikras ‘sure’ can function synonymously with the verb žinoti ‘to know’). Atypical usage is determined based on one or more of the features listed here.
Background. In the context of foreign language teaching methodology, post-text exercises play a key role in ensuring the effective acquisition of language material. These exercises are aimed at consolidating lexical and grammatical structures, developing reading and comprehension skills, as well as developing the ability to communicate spontaneously in a foreign language. The use of authentic materials in post-text exercises allows students not only to improve their language skills, but also to gain a deeper understanding of the cultural characteristics and context in which the language they are learning functions. Authentic texts provide students with the opportunity to familiarize themselves with real language situations and linguistic norms, which contributes to a more natural and organic language acquisition. The purpose of the study is to analyze the importance of post-text exercises in the process of learning a foreign language and demonstrate their role in consolidating acquired knowledge and improving students’ communication skills when using authentic materials. Materials and methods. The study examines examples of exercises presented in the Personal Management ESSD manual, designed for teaching English. Their detailed description is given, as well as an analysis of their role in improving communication skills and developing sustainable language competencies. Results. Post-text exercises based on authentic materials are an important component of foreign language teaching methods. They contribute not only to the consolidation of knowledge, but also to the development of communication skills, which is a necessary condition for achieving proficiency in a foreign language.
This article examines the cross-cultural features of lexical intensification in English and Uzbek political news discourse. The study investigates how journalists in both languages use intensifiers such as scalar adverbs, extreme adjectives, hyperbolic expressions, and culturally embedded evaluative units to shape ideological framing and influence audience perception. By comparing representative political news texts, the research identifies structural, semantic, and pragmatic similarities and differences in the use of intensified vocabulary. The findings show that English political discourse tends to employ graded lexical choices for subtle persuasion, whereas Uzbek discourse relies more heavily on emotionally charged and culturally resonant expressions. Overall, the analysis reveals how linguistic and cultural norms shape the communicative strategies of political media.
The presented article examines the temporal distance in artistic translation. By bringing ancient texts and works created in later eras to the modern reader, the translator acts, on the one hand, as a researcher and philologist, and on the other, as a creative writer reviving the image and characteristic flavor of the past. If the translation it presents to the modern reader does not convey the basic features of the environment described in the original and the cultural and historical conditions in which the work itself was created, then the artistic and aesthetic value of the work is reduced to nothing. In translation, the concept of time implies a calendar (historical) difference between the communicative conditions created by the original and those in which the translation takes place. J. Holmes believes that this problem can be solved in two main ways: historicization and modernization. The principle of historicization is considered in relation to the original, to the literary traditions to which it belongs. In this case, it is necessary to preserve vocabulary, style, rhythm and structure as much as possible. The modernization principle adapts the vocabulary and description of events in general to the modern era of the recipient of the transfer. However, the principle of modernization may be different: style, structure and vocabulary, as a rule, remain true to the original, while the lexical and thematic aspects of the text are clearly being modernized. One of the factors determining literary translation from the point of view of literary and artistic development is its repetition. This can be explained by several factors. The first is that the translation language becomes obsolete faster than the original language. The reason for the obsolescence of the language and the translation style is objectively explained by the change and development of expressive norms of the language. On the other hand, literary translation and the art of translation in general are constantly evolving, and the dynamics are putting forward new demands. In other words, a translation option that keeps up with the times is always in demand.
This study compares AI-generated texts (via ChatGPT) and student-written essays in terms of lexical diversity, syntactic complexity, and readability. Grounded in Communication Theory—especially Grice’s Cooperative Principle and Relevance Theory—the research investigates how well AI-generated content aligns with human norms of cooperative communication. Using a corpus of 50 student essays and 50 AI-generated texts, the study applies measures such as Type-Token Ratio (TTR), Mean Length of T-Unit (MLT), and readability indices like Flesch–Kincaid and Gunning-Fog. Results indicate that while ChatGPT produces texts with greater lexical diversity and syntactic complexity, its output tends to be less readable and often falls short in communicative appropriateness. These findings carry important implications for educators seeking to integrate AI tools into writing instruction, particularly for second-language (L2) learners. The study concludes by calling for improvements to AI systems that would better balance linguistic complexity with clarity and accessibility.
Emotions dynamically unfold and are jointly constructed throughout social interactions between individuals. Yet, how exactly the experience and expression of emotions interact throughout such interactions remains poorly understood. In this study, we investigated the interplay between the experience and verbal expression of negative affect within and between romantic partners during negative interactions. We examined this interplay in terms of four possible relations: (a) how one's experienced negative affect predicts the verbal expression thereof, (b) how the verbal expression of negative affect predicts a subsequent change in one's own experienced affect, (c) how the verbal expression of negative affect predicts change in a partner's experienced affect, and (d) how one's experienced negative affect predicts the verbal expression of negative affect by a partner. We answered these questions by analyzing second-to-second data of self-reported affect ratings and verbatim transcripts of videotaped negative interactions between romantic partners. Our findings reveal inconsistent evidence for intraindividual relationships between the experience and verbal expression of negative affect. Yet, they demonstrate a consistent, though small, interpersonal relation with the expression of negative affect in one partner predicting the subsequent experience of negative affect in the other. These results suggest that verbal negative emotion expression may be more consistently related to others' experience than one's own, and highlight the role of emotion expression in interpersonal emotion regulation and the social construction of emotional experience, though the small effect sizes suggest this relationship may be subtle and that many other factors contribute to our emotional experiences. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Hoarding Disorder (HD) is defined by the inability to discard objects until clutter becomes functionally impairing. A DSM-5 specifier for HD is lack of insight. A recent study found links between insight (using an objective clutter proxy) and inhibitory/cognitive control in HD. We aimed to explore associations between insight (using the same clutter proxy) and symptom severity, functioning, and cognition in Veterans with HD. 122 Veterans seeking treatment for HD completed pre-treatment assessments, including home-based assessments of clutter volume using the Clutter Imaging Rating Scale (CIR), HD severity measures, self-reported functioning, and neuropsychological testing. Insight was defined as the difference between the assessor and self-rating of the CIR (i.e., CIR-error). T-tests and regressions were used to evaluate the relationships between measures. The majority of the Veterans were older (m = 62), male (61 %), and White (57 %), with some college education. On clinical interview, only 10 % of the sample were rated with impaired insight. The mean CIR-error score was in the impaired range, with 47 % of the Veterans underreporting clutter. Lower HD severity and higher self-reported functioning were related to lower insight. Neuropsychological test performance was related to insight, but with small effects in varying directions. Nearly half of treatment-seeking Veterans demonstrated impairment in insight into levels of clutter, similar to previous work. Objective insight ratings demonstrated better sensitivity than clinician interviews for insight impairments. Lower insight was related to lower self-reported HD severity and higher self-reported functioning, raising the question of a potential insight paradox in HD.