Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
16504 papers
Recent studies demonstrate that visual working memory capacity is greater for real-world objects compared to simple features like colors and scrambled objects. This led to the proposal that conceptual meaning plays a critical role in structuring visual working memory (Chung, Brady, & Störmer, 2024). However, one challenge in comparing memory performance across stimulus sets is that they vary not only in conceptual meaning but also in perceptual similarity. Thus, some of the working memory benefits for real-world objects may arise from these perceptual differences – for example whether the visual system interprets inputs as objects or not. Here, we provide a strong test of this by using novel objects generated by generative adversarial networks designed to resemble real objects (Cooper et al., 2023), and compare memory performance across novel and familiar real-world objects. Across experiments, participants remembered sets of four objects drawn from one of four stimulus types: familiar objects, novel objects, scrambled familiar objects or scrambled novel objects. After a short delay, they completed a two-alternative-forced-choice task, selecting between a target and a foil object. Results revealed enhanced working memory performance only for familiar objects, with no differences among the other conditions. Importantly, convolutional neural networks analyses confirmed comparable perceptual similarities between familiar and novel objects relative to scrambled stimuli. Thus, although novel objects closely resembled familiar objects, they did not enhance memory performance. Further correlation analyses revealed that subjective familiarity ratings are correlated with memory performance for familiar objects, while low-level features like colorfulness are correlated with memory performance for novel objects, suggesting that visual memory relies on different aspects to best remember each stimulus type. Overall, these results demonstrate that “object-ness” alone is insufficient to enhance visual working memory. Instead, familiarity and conceptual knowledge are critical in improving working memory performance.
The meditation claims that it leads to better anti-inflammatory response and healthy aging by proper telomerase regulation. There are also benefits and positives in physical and mental health. The variety of diseases to be studied should be increased. It affects immunology, genetics and various aspects of physical and mental health including depression, substance abuse, eating disorders, conflict between couples, anxiety disorders and obsessive-compulsive disorder. Sit quietly and focus on your natural breathing or a word or mantra that you repeat silently. Let thoughts come and go without judgment and focus your attention on the breath or mantra. Physical sensations. Notice subtle physical sensations like itching or tingling without judgment and let them go. Pay attention to each part of your body sequentially from head to toe. Sensory. Pay attention to sight, sound, smell, taste and touch. Name them without judgment, such as “sights”, “sounds”, “smells”, “tastes” or “touch” and let them go. Human beings have between 12,000 and 50,000 thoughts per day, and 80 percent of them are negative. Emotional experiences deeply affect our physical states, for example, when we feel anger, our eyes close and our face burns. The training has positive effects on the physical and mental health of adults, such as reducing mood and anxiety disorders, distress and blood pressure. Magnetic alternating current stimulation applied at different frequencies (beta, theta and gamma) while theta and beta-tACS caused participants to rate emotional images as more pleasant (higher valence), while only theta-tACS reduced subjective arousal ratings (more calm). Regular practitioners have younger and brighter skin due to freedom from fear and stress.
Modern trends in digital communication exacerbate the problem of changing language norms under the influence of social networks, making the investigation of this issue particularly relevant. The purpose of the preset study was to identify and analyse transformations in language norms and usage as a result of the active use of social networks as the primary means of everyday communication. The study employed methods of linguistic observation, content analysis, and comparative analysis. The study revealed stable changes in written and oral communication caused by Internet communication: active use of slang, emojis, abbreviations, and Anglicisms; the study recorded an expansion of usage due to norms formed within online communities. The linguistic features of popular platforms (WhatsApp, Instagram, TikTok, Telegram) were analysed, as well as differences in the speech behaviour of users depending on their age and social context. The study found that the norms of online communication often contradict conventional literary norms, thereby influencing the formation of linguistic norms among young people. The data obtained also indicated the development of specific communication strategies driven by technical limitations and the functionality of various platforms, which leads to unique linguistic manifestations in each online community. Furthermore, the analysis revealed that the intensity and nature of language changes directly correlated with the level of user involvement in interactive forms of communication, such as commenting and taking part in discussions. The practical significance of the study lies in the possibility of applying its findings in educational and media teaching practice – in the development of training courses on modern linguistics, media literacy, as well as in the field of editing and translation
The translinguistic research paradigm contributes to the study of specific aspects of social interaction among multilingual language users. The multimodal and multisensory nature of language is manifested in language varieties including geographical, social, age or gender varieties. Human beings in the process of language contacts are very conscious of the relationship between race, nation and community on the one hand and language on the other, and the discrepancies between boundaries in linguistic structural terms and in socio-cultural and ideological terms. The object of the study is anglicisms used by the students of Don State Technical University in the media space from the point of view of highlighting their lexico-semantic characteristics and functioning. The aim of the research is to study the main trends in the use of anglicisms by students in social student networks. On the basis of the conducted online survey of 360 students of DSTU we tested hypotheses about the reasons and main trends in the use of anglicisms, the influence of students' specialization on their use in speech. The respondents' answers were divided into the following categories: 1) the most frequent anglicisms; 2) meanings of words; 3) spheres of application; 4) violation of the linguistic norm; 5) reasons for their usage; 6) prospects. We collected both quantitative and qualitative data, including surveys and observations. The results of the research indicate the tendency of frequent usage of direct borrowings and calques from English related to the sphere of “Internet” usage. Multilingual learners freely incorporate Anglicisms into their speech to overcome differences, discrepancies, inconsistencies and ambiguities in communication, manipulating them for strategic benefits when necessary. The use of anglicisms in the speech of the youth does not depend on their belonging to a professional community, with the exception of jargon and professional slang.
This paper examines how the Han script, as a non-phonographic and ideographic writing system, has historically mediated linguistic diversity in East Asia and how it continues to function as a site of negotiation between standardized national languages and vernacular or subaltern voices. Drawing on Jacques Derrida’s critique of phonocentrism and Gilles Deleuze and Félix Guattari’s theory of minor literature, the study argues that the Han script resists the phonographic imperatives of modern nation-states by retaining semiotic elasticity. Through this capacity, it enables the co-articulation of dominant and minor languages, allowing alternative modes of voice and subjectivity to emerge within its scriptural space. Case studies from Taiwan, particularly the diasporic Chinese communities in Taiwan and China illustrate how Han écriture enables both subversion and accommodation of linguistic norms, as seen in Liām-kua, Mahua literature, and scriptal visuality. These examples show that Sinophone expression is not merely a reaction to central authority but often operates within a hybridized field of cultural production that exceeds binary oppositions. Rather than conceptualizing Sinophone texts solely as resistance, the article proposes a reframing of scriptal mediation as an arena of affective, performative, and visual negotiation. It offers a new account of East Asian modernity as shaped not only by state-led language reform or colonial influence but also by the persistent pluralism encoded in the materiality of script. The Han script thus emerges not as a static emblem of tradition but as a dynamic infrastructure through which linguistic diversity is continuously voiced, managed, and reimagined.
Michael Riffaterre’s semiotic theory, with its emphasis on ungrammaticality and multi-layered reading, has provided an influential model for analyzing the distinctive structure of poetic language. This study investigates the application of Riffaterre’s semiotic framework to Qur’anic interpretation, with a specific focus on Angelika Neuwirth’s intertextual readings of the Qur’an. Neuwirth views the Qur’an as a poetic and dialogical text that engages with earlier religious and cultural traditions. She employs Riffaterre’s model to reveal the text's semantic depth and internal coherence through the notions of ungrammaticality and dual signification. Using Surah al-Ikhlāṣ as a case study, this paper critically evaluates Neuwirth’s application of Riffaterre’s theory by examining her treatment of the supposed “ungrammaticality” regarding the use of the word aḥad. The paper argues that the notion of ungrammaticality in the Qur’an can be reinterpreted not as a violation of linguistic norms, but rather as a semiotic cue that signals deeper intertextual and theological meanings. Accordingly, evaluating alleged irregularities requires a contextual analysis of lexical patterns across the entire Qur’an, where usage, frequency, and semantic range reveal a consistent theological logic. By integrating insights from classical Arabic grammar, lexicography, and tafsīr with modern semiotic theory, this study reassesses the scope and limits of applying Riffaterre’s model to sacred text analysis. It concludes that while semiotic and intertextual approaches can illuminate the Qur’an’s structural and semantic complexity, they must operate within a balanced hermeneutical framework that respects the text's revelatory nature and linguistic precision. Furthermore, this study demonstrates that the intentional utilization of ungrammaticality in the Qur’an effectively serves specific theological functions.
The article considers some features of the professional training of translators, namely the problem of developing cognitive flexibility. The insufficient study of this problem at the present stage determined the choice of the research topic. The objective of the article is to analyze the problem of cognitive flexibility of the translator and its formation in the process of training. Cognitive flexibility is the ability to quickly adapt one's thinking to new situations, change problemsolving strategies and switch between different concepts. Cognitive flexibility is important for intercultural communication, as it helps to effectively interact with representatives of different cultures. Therefore, cognitive flexibility is a key skill that ensures the efficiency, quality and accuracy of translation, helping to adapt to different working conditions and complex language situations. Translation is a complex cognitive process that requires instant analysis, interpretation and reproduction of the content in another language, taking into account the communicative context. The translator's activity is associated with the active work of mental processes, namely: attention, memory, analytical thinking, imagination, emotional regulation. The process of oral translation is especially intense, as it is necessary to maintain concentration, process large amounts of information and adapt in accordance with the cultural and linguistic norms of the target audience in conditions of limited time. The main approaches to the development of cognitive flexibility include educational, psychological, sociocultural, and neuropsychological approaches. Translation requires not only knowledge of languages, but also deep mental activity: understanding the context, subtext, emotional coloring, quick switching between languages, attentiveness, memory, imagination, analytical thinking. Psychological competence contributes to effective communication with clients.
State-Space Models (SSMs) have emerged as efficient alternatives to computationally intensive architectures like Transformers, particularly for sequence modeling. However, a fundamental challenge in their training is the reliance on static loss functions, which may not be optimal across all learning stages. To address this issue, in this paper a hybrid model integrating the Hyena architecture with a Dynamic Loss Network (DLN) is proposed which is guided by a Learn-to-Teach (L2T) approach (L2T-DLN). In this framework, the Hyena model is a student, and its loss function is optimized adaptively. A teacher model, leveraging a memory of the student's past performance, guides the DLN in dynamically balancing the primary cross-entropy loss and a regularization term. Experiments on the Penn Treebank (PTB) dataset show that our approach significantly improves language modeling performance. Our proposed model achieved a validation Perplexity of 102.6, a notable improvement over the 110.4 achieved by a baseline Hyena model using a static loss function. This research indicates that combining SSMs with adaptive loss function markedly enhances the quality and efficiency of deep learning models for sequential data, showing potential for applications in Natural Language Processing (NLP), time-series analysis, and biological signal processing.
This paper examines the vital role context plays in Interactional Sociolinguistics (IS) especially as it relates to cross-cultural miscommunications exemplified in British/American and Nigerian data. This study, therefore, critically investigates the intricate dynamics of how context shapes interactional communication, highlighting how cross-cultural differences, linguistic norms and societal expectations and contextualization cues often lead to semantic misrepresentation, misunderstandings and miscommunications. Drawing on empirical data from complex and linguistically diverse cultural background, the study demonstrates how Gumperz IS and contextualization theories can lighten-up the complex interplay between language, culture and context in cross-cultural sociolinguistic interactions. The study drew from purposively selected structured interviews involving electricians, bricklayers, teacher/pupils exchange and Head of Department/staff conversations, which were subjected to discourse analysis. The data reflect work environment across different regions, including USA, UK and Nigeria. The findings reveal that language is consequential in sociocultural context in which communication takes place, and also brings to the fore that effective cross-cultural communication requires not only linguistic competence but also a deep understanding of the cultural nuances and contextual factors that shape interactional dynamics. This paper also contributes to the unburdening of age-long perception that pragmatic context alone rather than cross-cultural differences often lead to miscommunication and distortion of intended meaning in interactional communication in an increasingly globalized world. Keywords: Interactional Sociolinguistics, Cross-Cultural Miscommunication, Contextualization Cues, Context, Cultural Differences.
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.
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.
Background: Color plays a pivotal role in visual perception, shaping emotions, attention, and cognition, particularly in art-related contexts. However, the influence of artistic training on color perception and neural processing remains poorly understood.Methods: This study examined differences in color perception between art and non-art groups using behavioral ratings and EEG data. Forty-four participants (22 art majors: 21.82 ±1.56 years old; 22 non-art majors: 20.73 ± 1.67 years old) with an equal gender ratio were recruited. Participants completed color perception tasks involving cool, warm, and neutral hues while EEG data were recorded with a 65-electrode system. Behavioral ratings and ERP components (P2 and P3) were analyzed, supplemented by decoding analysis to uncover neural processing patterns.Results: Behavioral data indicated that warm hues elicited higher emotional valence ratings than cool and neutral hues for both groups. EEG analysis revealed that warm and cool hues evoked larger P3 amplitudes compared to neutral hues. A group-hue interaction was observed in the P2 component, with the non-art group showing greater variability in P2 amplitudes across hues. Decoding analysis provided further evidence of distinct neural processing differences between the two groups.Conclusion: These findings demonstrate that color perception differs between art and non-art groups, particularly in the neural processing of the P2 component. Warm and cool hues elicit stronger emotional and attentional responses, highlighting distinct cognitive mechanisms influenced by artistic expertise.Keywords: ERP; color perception; P2; P3; artistic training
Despite established theoretical distinctions between passive verb forms and their constructions in contemporary academic and official texts (early 21st century) and in the linguistic practices of Ukrainian philology students, sentences featuring predicative forms ending in ‑но or ‑то often compete with sentences using predicative participles ending in ‑ний or ‑тий to express a resultative state following a prior action. This phenomenon has not yet been systematically examined within the news genre of media discourse. The study is relevant primarily because the media shape speakers’ linguistic tastes and their perception of linguistic norms. For linguists, it serves as a reliable source for observing the dynamics of linguistic change. News texts in online media represent two main types of relationships between sentences with predicative passive participles and sentences with predicative forms ending in ‑но, ‑то: the first type is characterised by the correlative pair ‘predicative passive participle – predicative form ending in ‑но/‑то’, while the second type is characterised by the use of these verb forms without correlation. Syntactic constructions with predicative participles ending in ‑ний, ‑тий and forms ending in ‑но, ‑то are mostly in correlative relationships. There are over 160 cognate pairs of ‘predicative passive participle – predicative form ending in ‑но/‑то’, which confirms their use as syntactic synonyms and as a means of avoiding structural monotony. The authors’ choice of a particular syntactic construction is determined by the tradition of identifying the morphological nature and syntactic function of passive verb forms. At the same time, simple sentences with predicative forms ending in ‑но, ‑то quantitatively prevail over two-part sentences with predicative passive participles, which coincides with the communicative orientation of news media texts to report on the completion of an action regardless of its performer and demonstrates the current trend of active use of syntactic constructions that are indigenous in origin and therefore natural for the Ukrainian literary language The limited use of passive verb forms that lack a correlative pair is attributed to the functional specificity of these lexemes in online media, in general, and in news media texts, in particular. The sporadic use of three-part compound sentences with predicative passive participles and non-standard three-part simple sentences with predicative forms ending in ‑но, ‑то attests to the orientation of the authors of news media texts towards restoring one of the distinctive syntactic features of the Ukrainian literary language – two-part sentences with a subject syntactic unit in the nominative case of a noun, if the agent is known and needs to be named. We envision the prospect of the completed study in further research into the dynamics of the relationship between syntactic constructions with predicative passive participles and forms ending in ‑но, ‑то in other genres of media discourse. Keywords: two-part sentences with passive participles in ‑ний, ‑тий, simple sentences with predicative forms in ‑нo, ‑тo, meaning of the effective state, syntactic synonyms, correlative pairs, media discourse.
Generic nouns such as Sache and Ding pose a challenge for semantic annotation due to their referential underspecification and context-dependent meaning. Although frequently classified under categories like {artefact} or {object}, their actual referents often belong to abstract or cognitive domains, as in Der Placeboeffekt ist eines der faszinierendsten Dinge in der Welt der Medizin. Drawing on valency grammar, this study shows that these nouns activate different argument structures depending on their syntagmatic environment, reflecting semantic flexibility and combinatorial variability. Lexical databases such as GalNet or GermaNet frequently assign multiple synsets to these nouns, illustrating their ontological ambiguity. This paper examines whether large language models (LLMs) can replicate this nuanced classification. Using a gold standard corpus annotated by linguists, we implement a two-step prompting strategy —supplying LLMs with predefined semantic tags and contextual windows— to test their performance. The results underscore the limitations of current LLMs in dealing with the lexical underspecification of generic nouns, even when provided with an extended context window. These findings contribute to ongoing discussions on the automation of semantic tagging and point to meaningful ways in which AI systems can complement human expertise in natural language processing tasks.
Pre-trained Language Models (PLM) have enabled a cost-effective approach to handling various downstream applications via Parameter-Efficient-Fine-Tuning (PEFT) techniques. In this context, service providers have introduced a popular fine-tuning-based product service known as Model-as-a-Service (MaaS). This service offers users access to extensive PLMs and training resources. With MaaS, users can fine-tune, deploy, and utilize their customized models seamlessly, leveraging a one-stop platform that allows them to work with their private datasets efficiently. However, this service paradigm has recently been exposed to the possibility of leaking user private data. To this end, we identify the data privacy leakage risks in MaaS-based PEFT and propose a Split-and-Privatize (SAP) framework, mitigating the privacy leakage by integrating split learning and differential privacy into MaaS PEFT. Furthermore, we propose Contributing-Token-Identification (CTI), a novel method to balance model utility degradation and privacy leakage. As a result, the proposed framework is comprehensively evaluated, demonstrating a 65% improvement in empirical privacy with only a 1% degradation in model performance on the Stanford Sentiment Treebank dataset, outperforming existing state-of-the-art baselines.
The article summarises the experience of prescriptive description of abbreviations in the Dictionary of Abbreviations of Russian as the State Language, which is being developed at the Russian Language Department of Donetsk State University. The difficulties of prescriptive description of this linguistic material are related to the absence of clear recommendations on the normative use of abbreviations in codifying sources (textbooks, grammars, dictionaries, etc.). D.I. Alekseev described the peculiarities of the pronunciation and inflection of abbreviations in the Russian language, but he did not propose uniform and obligatory rules. The absence of prescriptive recommendations on the pronunciation and inflection of abbreviations has led to the formation of a linguistic situation where abbreviations, which have become widespread among speakers and entered the language as independent lexemes, are used in speech according to their own rules, which are based on spontaneous speech practice. The compilers of the Dictionary of Abbreviations of Russian as the State Language attempted to solve the problem of integrating the general linguistic norm described by D.I. Alekseev and the established speech tradition of pronouncing lexicalised abbreviations. The recommendations proposed in the article relate to the pronunciation of initial, syllabic, mixed abbreviations and complex abbreviated words, the placement of stress in them, the determination of the gender of abbreviations and the possibilities of inflection. These recommendations are used in the lexicographical description of abbreviations, but they can also be used to form a set of rules for the use of abbreviations, the number of which is growing every day in modern Russian. The author separately considers the issue of lexicographical description of lexicalised abbreviations and the present-day tendency of stylistic neutralisation of inflected forms of lexicalised abbreviations. The author declares no conflicts of interests.
Decision-making in economic and moral contexts involves complex affective processes that shape judgments of fairness, responsibility, and conflict resolution. While previous studies have primarily examined behavioral choices in economic games and moral dilemmas, less is known about the underlying affective structure of these decisions. This study investigated how individuals emotionally represent economic (ultimatum game) and moral (trolley dilemma) decision-making scenarios using multidimensional scaling (MDS) and classification. Participants rated their emotional responses, including positive (pleased, calm, happy, peaceful) and negative (irritated, angry, gloomy, sad, fearful, anxious) affective states, to 16 scenarios varying by game type, the presence or absence of conflict, and intensity. MDS revealed two primary affective dimensions of distinguishing conflict from no-conflict and economic from moral scenarios. No-conflict-economic scenarios were strongly associated with positive affective responses, while the no-conflict-moral scenarios elicited heightened fear and anxiety rather than positive emotions. Increasing unfairness in the ultimatum game affected affective representation, while variations in the number of lives at stake in the trolley dilemma did not. Cross-participant classification analyses demonstrated that game type and conflict conditions could be reliably predicted from affective ratings, indicating systematic and shared emotional representations across participants. These findings suggest that economic and moral decisions evoke distinct affective structures, with fairness modulating conflict perception in economic contexts, while moral decisions remain affectively stable despite changes in intensity.
Passive voice remains a key grammatical structure for English learners, particularly in academic writing, yet many students struggle to use it accurately. This study analyzes the types of passive voice errors made by 19 fifth-semester students in the English Education Study Program at Tadulako University. Specifically, it addresses two questions: (1) How do classroom interaction patterns such as teacher-centered grammar instruction, limited student negotiation of meaning, or feedback practices shape students’ understanding and use of passive voice, and to what extent might these dynamics contribute to the dominance of developmental errors? (2) In what ways do students’ sociocultural backgrounds, prior educational experiences, and exposure to English outside the classroom influence their difficulties with auxiliary verbs and tense agreement, and how do these factors mediate tensions between Indonesian linguistic norms and English academic writing conventions? A quantitative design was employed, with a test focusing on passive constructions in present continuous, past continuous, and past perfect tenses. Students’ responses were categorized using Dulay et al.'s (1982) comparative taxonomy of developmental and interlingual errors. Results revealed developmental errors as the most prevalent (89.9%), mainly involving incorrect auxiliary verbs (is, am, are, being, been), past participle formation, and tense agreement. These findings highlight the need for targeted grammar instruction on auxiliary patterns and participles, alongside enhanced practice, corrective feedback, and adjustments to classroom interactions and sociocultural considerations to boost accuracy.
This article explores the critical engagement of two academics who confront lived experiences with the institutional and tangible dimensions of linguistic barriers and discrimination in the Portuguese district of Faro. Centred on the challenges posed at the border, the study fits into the wider framework of mobilities between North Africa and southern Europe, and attempts to demonstrate how language, as a form of social practice, impacts access to employment, education and society at large. Portuguese emerges as a dual entity: an institutional barrier, a form of socio-spatial control that reinforces exclusion, illustrating exclusionary processes within hierarchies and structural violence; a transnational bridge that fosters belonging and, simultaneously, a battleground where identity and self-determination face the constraints imposed by the economic, social, and political order that impact Moroccan migration to southern Portugal. The research highlights the imbrications of the undervaluation of migrants' cultural knowledge, the ambivalence of linguistic identity within a globalized world, exacerbating social exclusion, and systemic discrimination of non-privileged migrants in a polarized region shaped by social and economic asymmetries and increasingly representative nationalisms. From a systemic justice perspective, this devaluation reinforces structural inequalities, marginalizing those who do not conform to dominant linguistic norms. The national languages’ role as linguistic and cultural gatekeeper exemplifies the intersection of identity construction and socio-political hierarchies in the context of mobilities. This study, grounded in a collaborative project blending autobiography and biographical research, employs qualitative methods, including biographic interviews, ethnographic observation, and critical human rights studies.
The article is devoted to studying socially determined linguistic processes, which are traditionally associated with the broad problem of social variation of communication (discourse) and linguistic variability of the German language. It presents the results of a study conducted within the framework of cognitive sociolinguistics - the linguistics of social meanings. The author observes continuity in the development of scientific thought, explores the problem of linguistic variability in two modes - theoretical and applied. The subject of the research is the terminological apparatus and specific linguistic facts that are based on the cognitive, communicative and social functions of language, that is, to be the reality of the thought of individual and/or collective knowledge of representatives of a certain society and the means of their communication. The purpose of the article is to analyze theoretical propositions, linguistic terms and existing specific language forms that convey social meanings, marked by a social feature in their terminological interpretations with a focus on the linguistic picture of the Germany new lands. The novelty of the research lies in cognitive-semantic analysis, systematization and modeling this phenomenon in the social aspect. As a result, the author comes to her own conclusions, which lead to understanding and rethinking the old views on the problems of dialectology in the context of modern realities of the German language society and the data of modern linguistics. The methodology of the research and the description of its results are determined by the principle of interdependence of the three most important didactic and linguistic strata - the study of modern language from the standpoint of linguistic norms, the study of linguistic variability and the analysis of language change in the framework of its historical development. General scientific methods and special methods of cognitive linguistics are used to analyze theoretical material and linguistic facts, including explanatory description, interpretation, cognitive modeling, cognitive dominance, and focusing.
The article explores irony as a complex linguistic and pragmatic phenomenon that plays a significant role in creating satirical effect within the sketch genre. The object of analysis is the sketch «Les Flics» by French comedian Coluche, in which irony functions as a tool of social critique, particularly through the ridicule of flaws within the institution of police. The study identifies the main linguistic, stylistic, and pragmatic means used to construct irony. It demonstrates that the central communicative strategy shaping the critical attitude toward the police system is the deliberate provocation of the audience and the emphasis on the absurdity of the depicted social conditions. The comic effect arises from the contrast between socially expected norms of behavior (including verbal conduct) and the reality represented by the narrator-character. Stylistic devices such as antiphrasis, metaphor, metonymy, grotesque, and sarcasm, along with linguistic features such as colloquial register, slang, and violations of linguistic norms, are shown to contribute to the portrayal of deep linguistic and social deviation in the police character. The article draws on contemporary linguistic theories, including pragmatics, speech act theory, polyphony theory, and relevance theory. It concludes that irony in the sketch is both staged and situational, with the comic effect emerging from the conflict between expectation and reality. Special attention is given to implicature, polyphonic structure of the utterance, and the satirical function of the narrator. The study shows that irony not only enhances the aesthetic dimension of the text but also performs a socially critical function by shaping a discourse of resistance. Future research directions include the analysis of other Coluche sketches in the context of linguistic critique of society.
Abstract This paper presents a novel framework for modeling role and task allocation in cooperative wheeled soccer robot systems by leveraging latent knowledge extracted from past collaborative interactions. Inspired by recent advances in heterogeneous multi-robot collaboration, the proposed method encodes a soccer team as a set of Multidimensional Relational Structures (MDRSs), capturing both temporal and spatial relations among robot roles, actions, and stimuli. A structured dataset, termed the Soccer Robot Collaboration Treebank (SRCT), is introduced to represent play-by-play histories of robot behaviors, parsed through a formal grammar to support structured learning. Probabilistic modeling and Non-Negative Tensor Decomposition (NTD) are applied to the resulting tensors, enabling robust inference and latent knowledge estimation even in scenarios with sparse data or communication loss. Simulated experiments using a team of wheeled soccer robots in the Webots environment demonstrate the system’s ability to dynamically reassign roles, reason over incomplete histories, and predict collaborative behaviors such as passing, defending, or role-switching. The results show that the proposed framework enhances both strategic flexibility and robustness, providing a foundation for real-time decision-making in robotic soccer under uncertainty.
Mood, an individual’s emotional state, fundamentally shapes how the brain interprets sensory input by providing a continuous affective context for prediction and evaluation. In language processing, mood may bias the interpretation of emotionally valenced words, amplifying or dampening their perceived affect. Yet, the temporal dynamics of these mood-valence interactions remain poorly understood. To clarify inconsistent evidence on the timing and nature of mood-valence interactions, we examined how induced mood influences early stages of emotional word processing using EEG. Participants performed a valence-rating task for positive, negative, and neutral words in a baseline condition and following positive or negative mood induction. Event-related potentials were analysed across early processing windows (N1, P2, EPN) using cluster-based permutation statistics. Positive mood selectively attenuated N1 amplitudes for highly valenced words, consistent with reduced prediction error under mood-congruent expectations. Later components (P2, EPN) showed decreased amplitudes for both high and neutral valence, suggesting reduced model updating under mood-congruent expectations. Negative mood, in contrast, produced weaker and temporally delayed modulations. Behaviourally, participants responded more quickly to valenced words under induced mood conditions, supporting the neural findings. Interpreted within a predictive coding framework, these results support the theoretical view that mood functions as a hyperprior, tuning the precision of predictive models during language comprehension. Positive mood appears to enhance predictive flexibility and facilitate the processing of affectively congruent words, whereas induced negative mood reduces positive affect. Taken together, the findings highlight how affective states dynamically modulate early predictive mechanisms in emotional language processing.
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.
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.
The obligatory use of third-person honorifics is a distinctive feature of several South Asian languages, encoding nuanced socio-pragmatic cues such as power, age, gender, fame, and social distance. In this work, (i) We present the first large-scale study of third-person honorific pronoun and verb usage across 10,000 Hindi and Bengali Wikipedia articles with annotations linked to key socio-demographic attributes of the subjects, including gender, age group, fame, and cultural origin. (ii) Our analysis uncovers systematic intra-language regularities but notable cross-linguistic differences: honorifics are more prevalent in Bengali than in Hindi, while non-honorifics dominate while referring to infamous, juvenile, and culturally exotic entities. Notably, in both languages, and more prominently in Hindi, men are more frequently addressed with honorifics than women. (iii) To examine whether large language models (LLMs) internalize similar socio-pragmatic norms, we probe six LLMs using controlled generation and translation tasks over 1,000 culturally balanced entities. We find that LLMs diverge from Wikipedia usage, exhibiting alternative preferences in honorific selection across tasks, languages, and socio-demographic attributes. These discrepancies highlight gaps in the socio-cultural alignment of LLMs and open new directions for studying how LLMs acquire, adapt, or distort social-linguistic norms. Our code and data are publicly available at https://github.com/souro/honorific-wiki-llm
<span lang="EN-US">The illicit act of appropriating programming code has long been an appealing notion due to the immediate time and effort savings it affords perpetrators. However, it is universally acknowledged that concerted efforts are imperative to identify and rectify such transgressions. This is particularly crucial as academic institutions, including universities, may inadvertently confer degrees for work tainted by this form of plagiarism. Consequently, the primary objective of this research is to scrutinize the feasibility of identifying plagiarism within pairs of Verilog algorithms and texts. this study aims to detect plagiarism in textual content and Verilog code by leveraging diverse linguistic characteristics from the WordNet lexical database. The primary objective is to achieve optimal accuracy in identifying instances of plagiarism, incorporating features such as modifications to text structure, synonym substitution, and simultaneous application of these strategies. The system's architecture is intricately designed to unveil instances of plagiarism in both textual content and Verilog code by extracting nuanced characteristics. The systematic process includes preprocessing, detailed analysis, and post-processing, supported by a feature-rich database. Each entry in the database represents a distinctive similarity case, contributing to a thorough and comprehensive approach to plagiarism detection.</span>
Word Sense Disambiguation (WSD) is a fundamental task in Natural Language Processing (NLP), addressing the challenge of identifying correct word meanings in context. This task is particularly complex for morphologically rich and resource-limited languages like Hindi, which exhibit significant lexical ambiguity compounded by limited availability of annotated corpora. To address these challenges, we propose a supervised approach combining the multilingual BERT model (mBERT) with Hindi WordNet as a structured lexical resource. Using few-shot learning, we fine-tune mBERT on a dataset constructed from Hindi WordNet to disambiguate contextually ambiguous words across four parts of speech (POS): nouns, verbs, adjectives, and adverbs. Experiments on standard Hindi WSD benchmarks demonstrate that our method significantly outperforms traditional rule-based and embedding-based approaches, achieving 96.48% accuracy—an approximate 3% improvement over the strongest baseline. These results validate the effectiveness of integrating contextualized embeddings from pre-trained language models with structured lexical databases, highlighting the promise of hybrid techniques for advancing WSD in low-resource languages and providing a framework applicable to other morphologically complex languages with similar resource constraints.
This study reviews the English language test of Singapore’s Primary School Leaving Examination, a high-stakes national assessment taken annually by nearly all primary six students for secondary school placement. Given the test’s importance in shaping students’ academic pathways and recent format changes, it is crucial to evaluate its validity, specifically its ability to provide accurate and fair assessments of students’ English language proficiency and academic readiness. The review outlines the test’s educational and policy context, followed by a description of the latest formats for both the English language and foundation English language versions. The analysis focuses on core dimensions of test validity, including content representativeness, construct validity, criterion-related validity (concurrent and predictive), and reliability (inter-rater reliability and internal consistency). Drawing on official documents and limited empirical studies, the review finds moderate improvements in content representativeness and construct validity. However, both longstanding and emerging concerns (e.g., the exclusion of local linguistic norms and genre scope) indicate that key limitations remain. While predictive validity, inter-rater reliability, and internal consistency appear supported, empirical research remains sparse across all reviewed test qualities, particularly in concurrent validity. The review integrates identified research gaps and proposes inquiry directions to inform future test development and policy adaptation. Strengthening the evidence base is essential for ensuring a valid, reliable, and equitable assessment system in Singapore’s primary education landscape.
Introduction Researchers working in the field of cognitive aging frequently encounter highly motivated yet nervous older participants during data collection in the laboratory. Such anecdotal experiences raise the question of whether the affective or physiological response of older participants to psychological laboratory experiments differs to that of young adults, who might be less motivated but also less nervous, as they may be more used to the environment and to learning and memory tests. Methods In the present study, we collected saliva samples and subjective affective ratings during an EEG experiment on memory, and at home, in young and older adults, while also taking into account sex effects. Results There was no significant interaction involving time point (laboratory vs. at home) and age group. However, across both time points older males showed significantly higher cortisol-levels than older females, while there was no difference for younger males and females. The trajectories in cortisol levels throughout the session, especially around the memory task, differed by age: While there was a decrease in cortisol levels for younger adults from before to after the memory task, we did not observe such a decrease in older participants. There were few age differences in alpha-amylase or negative affect. However, older adults showed higher ratings of positive affect than younger participants. Importantly, lower cortisol levels before the memory task were associated with higher associative memory performance for older adults. Discussion Affective reactions to psychological laboratory tasks may hence be an important factor to consider in psychological experiments in the field of cognitive aging.
Lexical Semantic Change (LSC) provides insight into cultural and social dynamics. Yet, the validity of methods for measuring different kinds of LSC remains unestablished due to the absence of historical benchmark datasets. To address this gap, we propose LSC-Eval, a novel three-stage general-purpose evaluation framework to: (1) develop a scalable methodology for generating synthetic datasets that simulate theory-driven LSC using In-Context Learning and a lexical database; (2) use these datasets to evaluate the sensitivity of computational methods to synthetic change; and (3) assess their suitability for detecting change in specific dimensions and domains. We apply LSC-Eval to simulate changes along the Sentiment, Intensity, and Breadth (SIB) dimensions, as defined in the SIBling framework, using examples from psychology. We then evaluate the ability of selected methods to detect these controlled interventions. Our findings validate the use of synthetic benchmarks, demonstrate that tailored methods effectively detect changes along SIB dimensions, and reveal that a state-of-the-art LSC model faces challenges in detecting affective dimensions of LSC. LSC-Eval offers a valuable tool for dimension- and domain-specific benchmarking of LSC methods, with particular relevance to the social sciences.
Knowledge distillation (KD) is a widely adopted technique for compressing large models into smaller, more efficient student models that can be deployed on devices with limited computational resources. Among various KD methods, Relational Knowledge Distillation (RKD) improves student performance by aligning relational structures in the feature space, such as pairwise distances and angles. In this work, we propose Quantum Relational Knowledge Distillation (QRKD), which extends RKD by incorporating quantum relational information. Specifically, we map classical features into a Hilbert space, interpret them as quantum states, and compute quantum kernel values to capture richer inter-sample relationships. These quantum-informed relations are then used to guide the distillation process. We evaluate QRKD on both vision and language tasks, including CNNs on MNIST and CIFAR-10, and GPT-2 on WikiText-2, Penn Treebank, and IMDB. Across all benchmarks, QRKD consistently improves student model performance compared to classical RKD. Importantly, both teacher and student models remain classical and deployable on standard hardware, with quantum computation required only during training. This work presents the first demonstration of quantum-enhanced knowledge distillation in a fully classical deployment setting.
This paper examines how social media discourse affects the learning of the English language on the tertiary level in Lahore and how informal online communication influences the academic English of students in Lahore. The qualitative design was employed to gather data on the basis of semi-structured interviews with English language learners and teachers. Braun and Clarke’s (2006) framework was used to conduct thematic analysis on the transcribed data. The results indicate that though social media provides appropriate exposure to vocabulary, pronunciation, and language use in real life, the casualness of linguistic norms has a very strong impact on the students’ academic writing and their communicative accuracy. The participants claimed to use short forms, abbreviations, slang and mixed-language texting on a regular basis, and these transferred to essays and presentations. Other themes were distraction and a lack of studying discipline, the inability to stick to the formal register, and the misunderstanding of words acquired in unconfirmed online situations. Teachers also reported on the same lines, as they observed poor writing standards in academic writing and increased dependence on social-media-driven language patterns. Pedagogical mechanisms to counteract these effects were also determined in the study with the focus being on register awareness, purposeful digital task integration, and curriculum modernization. On the whole, the study has determined that the power of social media is twofold, both positive when moderated and negative when uncontrolled and recommends that informed teaching and learning methods are needed to help students balance between informal online communication and formal academic language.
Background and objective Navigating interprofessional team dynamics is essential for high-quality patient care in pediatric settings. This study involved medical students on a pediatric clerkship who explored the characteristics of high- and low-performing clinical teams by considering drivers and barriers to effective team performance. By analyzing these reflections, the study aimed to identify key facilitators and barriers to effective team-based care. Methods Survey evaluations and narrative reflections were completed by third-year students (M3s) at a single US allopathic medical school during their pediatric clerkship after receiving training in TeamSTEPPS® and Institute for Healthcare Improvement (IHI) Open School, two programs that support quality improvement (QI) in healthcare. Descriptive statistical and inductive thematic analyses were conducted on the resulting 183 narratives. A valence rating system was employed to quantify narrative responses as positive/attractive or negative/aversive, with a Cronbach alpha of 0.958 between two independent reviewers. Results Inductive thematic analysis generated 40 themes that we grouped under the five TeamSTEPPS® skill domains (situation monitoring, communication, leadership, team structure, mutual support) into thematic conceptual models. High-performing teams demonstrated open communication, role clarity, shared understanding, and organized task delegation. Low-performing teams displayed a lack of information exchange, uncertain team roles, unhealthy power dynamics, and disorganized task delegation. Conclusions After instruction in QI methods, pediatric clerkship students identified consistent drivers of and barriers to effective team performance. The themes within the narrative reflections can provide insights into improving patient care delivery, specifically around situation monitoring, communication, and team structure.
Deep neural networks employ specialized architectures for vision, sequential and language tasks, yet this proliferation obscures their underlying commonalities. We introduce a unified matrix-order framework that casts convolutional, recurrent and self-attention operations as sparse matrix multiplications. Convolution is realized via an upper-triangular weight matrix performing first-order transformations; recurrence emerges from a lower-triangular matrix encoding stepwise updates; attention arises naturally as a third-order tensor factorization. We prove algebraic isomorphism with standard CNN, RNN and Transformer layers under mild assumptions. Empirical evaluations on image classification (MNIST, CIFAR-10/100, Tiny ImageNet), time-series forecasting (ETTh1, Electricity Load Diagrams) and language modeling/classification (AG News, WikiText-2, Penn Treebank) confirm that sparse-matrix formulations match or exceed native model performance while converging in comparable or fewer epochs. By reducing architecture design to sparse pattern selection, our matrix perspective aligns with GPU parallelism and leverages mature algebraic optimization tools. This work establishes a mathematically rigorous substrate for diverse neural architectures and opens avenues for principled, hardware-aware network design.
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.
The deployment of large language models (LLMs) across heterogeneous environments requires format-specific conversion, precision tuning, and consistent evaluation-tasks that are often fragmented across multiple tools. This work presents SOLO-Export, a unified command-line interface (CLI) framework for multi-format export and post-export benchmarking of causal LLMs. Having precision options for FP16 and INT8 where appropriate, the system supports the ONNX, TorchScript, Hugging Face, TensorFlow Lite, and TensorRT backends. Device-aware exports for both CPU and CUDA targets are made possible by a configuration-driven workflow that generates artifacts in a uniform directory structure. Each exported model is benchmarked using the Penn Treebank dataset by the integrated evaluation harness, which reports inference latency, token-level accuracy, and perplexity. According to experimental results, FP16 exports on GPU-oriented backends like TensorRT achieved up to 3.2 times lower latency than baseline FP32 models. On the top of that, with minimal impact on perplexity, storage size was reduced by more than 60% thanks to INT8 quantization. The combined approach reduces manual configuration overhead, speeds up deployment preparation, and ensures consistent performance insights across formats. This study demonstrates that a single, scalable pipeline can be effective.
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.
This preregistration describes a within-subjects experiment investigating whether and how cultural priming would influence emotional valence ratings among unbalanced Mandarin–English bilinguals immersed in an L2 environment. Participants rate positive, negative, and neutral words in three cultural contexts (no context, native culture, second culture). We hypothesise that activating either native or second culture will enhance the extremity of valence ratings, compared to the no context baseline, with stronger effects when the native (Chinese) culture is primed. Trial-level valence ratings will be analysed using a linear mixed-effects model with fixed effects of Culture, Valence, and their interaction.
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.
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
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.
This paper presents the structure and principal components of the linguistic resources required for sentiment analysis in the Uzbek language. The research aims to identify and develop effective approaches for constructing a linguistic database - referred to as SentiUzNet - and to establish a foundational sentiment lexicon tailored specifically to the characteristics of the Uzbek language. In particular, the paper discusses key principles for annotating words with sentiment polarity and subjectivity scores, as well as methodological foundations for building a lexicographic database to support automated emotional analysis of texts. A significant part of the research focuses on experimenting with large-scale user-generated content, specifically social media comments written in Uzbek. These datasets were used to train and evaluate sentiment analysis models, thereby allowing an assessment of their performance and practical applicability. The results of this research represent one of the first comprehensive attempts to facilitate automatic sentiment detection in the Uzbek language and are expected to contribute substantially to the advancement of natural language processing technologies in under-resourced linguistic settings.
Large language models (LLMs) have reignited debate about whether machines without minds or intentions can genuinely participate in linguistic practice. Critics portray them as ‘stochastic parrots’ that manipulate form without meaning, whereas defenders emphasize their impressive functional capacities. This paper argues that these disputes conflate distinct dimensions of meaning and agency. I extend Huw Price’s distinction between i-representation and e-representation (roughly, inferential versus environment-tracking types of representation) by differentiating physical e-representation—such as a fuel gauge, grounded in causal coupling—from symbolic e-representation, exemplified in language and mediated by agents. This refinement clarifies what is at issue: LLMs clearly display i-representational competence through their participation in inferentially structured discourse. Whether their outputs possess symbolic e-representational content, however, is contested and framework-relative. It depends on whether agent-mediated uptake is taken to suffice, or whether additional grounding conditions—such as intentions, causal connections, or proper functions—are required. I further distinguish norm-sensitivity—the capacity to track and adapt to linguistic norms, which grounds their i-representational competence—from norm-responsibility, the reflexive capacity to own commitments and bear accountability. Technical analysis of LLM architectures shows that they exhibit advanced norm-sensitivity through statistical learning but entirely lack norm-responsibility. LLMs thus occupy a distinctive position: they are genuine functional participants in linguistic practices, yet fall short of the reflexive agency characteristic of responsible speakers.
This study explores the syntactic network characteristics of English e-commerce live-streaming discourse by employing a syntactic treebank and syntactic complex network analysis. The main findings are: (1) The syntactic network of English e-commerce live-streaming discourse exhibits small-world and scale-free properties, which are hallmark traits of complex networks. (2) The central nodes of the network are be, I, and the, with be serving as the most central node, while I and the act as local central nodes. (3) The central node be demonstrates both strong centrifugal and centripetal forces. Its centrifugal force is most frequently associated with subject relations and adjective complements, while its centripetal force is characterized by auxiliary and clausal complements. These findings indicate that the syntactic structure of English e-commerce live-streaming discourse is highly robust. This robustness underscores the discourse’s functional purpose: to convey information clearly while engaging users through personalization and specificity. Furthermore, the study highlights the critical role of be in attributive and descriptive constructions. Overall, this research provides insights into the syntactic organization of e-commerce discourse and demonstrates the effectiveness of complex network analysis in linguistic studies.
BACKGROUND AND OBJECTIVES: It is well documented that the fear of specific stimuli and situations can be acquired through the social observation of the actions of another person. In contrast, it is still a matter of debate, whether processes related to fear attenuation, extinction, and extinction-retrieval can equally be achieved through social observation after de novo fear conditioning. METHODS: Here, we used a differential fear conditioning procedure and investigated whether the variation of the context of video-based vicarious extinction learning (VEL) will affect subsequent extinction learning and extinction-retrieval. Conditioned fear acquisition, extinction, and extinction-retrieval was measured using psychophysiological (skin conductance responses) and subjective measures (CS-UCS contingency ratings and CS-valence ratings). RESULTS: Participants showed enhanced fear extinction learning after VEL as compared to controls. VEL improved extinction learning relative to controls but appeared to be highly context-dependent. The beneficial effect of VEL on subsequent extinction learning was abolished when the context in which the model was performing in the video was different from the context in which the observer performed all stages of the experiment. LIMITATIONS: Data were obtained in a non-clinical sample which does not permit the extrapolation of findings to clinical populations. CONCLUSION: Our results suggests that safety information derived from VEL promotes fear extinction when model and observer perform the experiment in the same context. Given that fear extinction is considered as an experimental proxy of exposure therapy, our findings might be instructive for the development of novel clinical interventions to promote exposure treatment efficacy.