Papers reviewed and determined not to be word norm studies. Use the flag icon to report errors or suggest re-inclusion.
18265 papers
This paper examines the growing ideological dissonance between the contemporary political left and the working-class constituencies it historically claimed to represent. Drawing on sociological and political science literature alongside comparative evidence from Brazil, the United States, France, and the United Kingdom, we argue that the left’s progressive drift toward university-incubated identity politics—including debates over linguistic norms, gender categories, and minority group identity—has produced a profound semantic and cultural rupture with lower-income voters whose priorities remain rooted in economic security, family cohesion, and social conservatism. Simultaneously, right-wing and populist movements have strategically occupied the abandoned terrain of class-based discourse, reframing their appeal in the language of workers, families, and everyday material hardship. We analyze the semantic transformation of the terms left and right, the phenomenon of cancel culture as a mechanism of epistemic coercion, the paradox of conservative sociality among the poor, and the structural conditions that produce what we term displacement populism—the rightward migration of voters who were once natural constituents of progressive politics. We conclude with reflections on the prospects for political realignment and the conditions under which left-wing movements might recover their original social mandate.
We introduce BeDiscovER (Benchmark of Discourse Understanding in the Era of Reasoning Language Models), an up-to-date, comprehensive suite for evaluating the discourse-level knowledge of modern LLMs.BeDiscovER compiles 5 publicly available discourse tasks across discourse lexicon, (multi-)sentential, and documental levels, with in total 52 individual datasets.It covers both extensively studied tasks such as discourse parsing and temporal relation extraction, as well as some novel challenges such as discourse particle disambiguation (e.g., "just"), and also aggregates a sharedtask on Discourse Relation Parsing and Treebanking for multilingual and multi-framework discourse relation classification.We evaluate open-source LLMs: Qwen3 series, DeepSeek-R1, and frontier reasoning model GPT-5-mini on BeDiscovER, and find that state-of-the-art models exhibits strong performance in arithmetic aspect of temporal reasoning, but they struggle with long-dependency reasoning and some subtle semantic and discourse phenomena, such as rhetorical relation classification.
Music has a well-documented capacity to influence emotional, physiological, and behavioral states, making it a powerful medium for shaping human experience. A fundamental characteristic underlying many of these effects is predictability: listeners continuously form expectations about upcoming musical events based on learned regularities in musical structure. When music confirms or violates these expectations, it can meaningfully shape the listener’s perceptual and emotional experience. Therefore, variations in melodic predictability, ranging from highly regular, familiar patterns to more unexpected or ambiguous sequences, can be expected to differentially affect listeners’ internal states. The objective of this study is to investigate the influence of melodic predictability on subjective and physiological arousal in healthy older adults. Using a within-subject experimental design, 71 older participants listened to melodies varying in melodic predictability while subjective arousal was assessed using a visual analogue scale (VAS), alongside continuous psychophysiological measures of electrodermal activity (EDA) and heart rate (HR). Linear mixed model analyses indicated small but significant effects on subjective arousal ratings and on EDA, indicating psychological and sympathetic effects of melodic predictability. HR results, however, showed small but not significant effects. These findings help us understand melodic predictability as a characteristic of music in influencing arousal in older adults, which may inform the field of music therapy for clinical populations including older adults with dementia. Further research is needed to explore how musical predictability contributes to arousal regulation as a mechanism for supporting older adults with dementia.
Dictionaries have historically served as instruments of linguistic standardisation and national consolidation, with the Oxford English Dictionary ( OED ) standing as a paradigmatic example of this function. However, Han Shaogong’s A Dictionary of Maqiao subverts this role through its fictionalised lexicon format. Narrated by an Educated Youth sent to the fictional village of Maqiao, the novel compiles an idiosyncratic dictionary shaped by local dialects and cultural practices, opposing the homogenising aims of official lexicography. Han’s playful allusion to the OED – through the invented place-name “Maqiao” (literally, “horse-bridge”) – invites a satirical comparison with Oxford, foregrounding the novel’s challenge to dominant linguistic and lexicographic models epitomised by the OED. While the dictionary format of DMQ has been explored in previous scholarship, this chapter introduces a new dimension by analysing Julia Lovell’s English translation. It argues that Lovell’s version, which adapts the indexing from stroke-based to alphabetical order, inadvertently marginalises the novel’s local particularities and reflects the broader hegemonies of alphabetic, Western-centric linguistic norms. By tracing DMQ ’s friction with both the OED and its English translation, this chapter situates the novel within a transnational discourse of translation, literature and modernity, demonstrating how Han’s work contests the imagined coherence of language and history by foregrounding the improvised, the unfamiliar, and the minor.
Swallowing is tightly coupled with emotion-autonomic states, while olfactory pathways project to limbic and hypothalamic hubs that can enhance parasympathetic activity and reduce stress. Whether a pleasant natural-wood odor can modulate swallowing-related brain activity and behavior remains unclear. To test whether Hinoki (Japanese cypress) inhalation improves affective ratings and increases the repetitive saliva swallowing test (RSST) difference (post-pre; swallows/30 s), and whether it suppresses swallowing-related activity in the premotor cortex (Brodman area 6 (BA6)) and the hypothalamus. The effects of exploratory whole-brain and interaction between Task and Odor were also evaluated. In a randomized within-subject crossover with a one-week interval, participants inhaled Hinoki essential oil or odorless rice-oil control. We assessed brain activity during voluntary saliva swallowing using functional magnetic resonance imaging (fMRI). Outcomes included subjective ratings (odor intensity, preference, comfort, recollection) and RSST counts per 30 s; RSST difference was computed as post-pre inhalation. Hinoki improved affective ratings and increased RSST difference compared to control. The odor main effect showed reduced activation in three regions-bilateral BA6 and the hypothalamus. An interaction effect between Task (swallowing vs. rest) and Odor (Hinoki vs. control) was found in the right putamen. The pattern supports a model: odor-induced autonomic calming (lower heart rate, reduced hypothalamic activity) lowers premotor load and improves swallowing, reflected in RSST difference. These findings suggest that aromatherapy-assisted dysphagia rehabilitation using olfactory priming-particularly for patients with post-stroke sequelae or post-stroke depression with poor appetite-may help enhance training efficiency and recovery.
= 702), we examined whether the expectancy of an action effect shapes the affective evaluation of corresponding action-effect episodes. In each study, participants responded to stimuli by clicking on buttons that produced effects with either high (stimulus-congruent) or low (stimulus-incongruent) expectancy. Induced affect was assessed using both implicit (affective priming) and explicit (valence ratings) measures. Overall, high-expectancy episodes elicited relatively more positive affect than low-expectancy episodes. For our implicit measure, this effect persisted unless correspondence among all task events (stimulus, response, and effect) was simultaneously reduced (Experiments 2 + 3). Furthermore, this outcome could not be attributed to mere visual mismatch between stimulus and effect (Experiment 4) and was observed even when stimulus-congruent effects were less likely to occur than stimulus-incongruent ones (Experiments 5 + 6). These findings suggest that expected action outcomes elicit positive affect, thus offering a parsimonious explanation for performance advantages previously attributed to more complex mechanisms like ideomotor accounts or response monitoring. More broadly, we propose that affective evaluation of action-effect episodes represents a fundamental mechanism governing behavior across multiple psychological domains, from basic action control to complex behavior in various settings. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
Open-vocabulary image classification can recognize arbitrary textual categories but often fails to capture hierarchical relationships, for example, a Ragdoll cat should also be recognized as both cat and animal. Therefore, we introduce OpenHier, a comprehensive framework for open-vocabulary hierarchical classification that encompasses a hierarchical structure, a dataset, a benchmark, and a model. To capture hierarchical relationships, we construct a systematic real-world hierarchical structure based on the linguistic lexical database WordNet and Vision-Language Large Model. Building upon this structure, we develop a large-scale dataset with 4M annotated images, as well as a benchmark with 50K annotated images. Meanwhile, we design an evaluation pipeline to assess open-vocabulary hierarchical classification performance using several curated metrics. Furthermore, we propose a hierarchical consistency constraint method and multimodal alignment strategy to build a hierarchical classification model. Comprehensive experimental results demonstrate that our model achieves superior performance on both multi-label image classification and hierarchical image classification tasks in the open-vocabulary setting.
Abstract Recent advances in text-to-music (TTM) generation have enabled controllable and expressive music creation using natural language prompts, yet the extent to which these systems faithfully convey intended emotions remains largely underexplored. In this study, we introduce AImoclips, a benchmark designed to evaluate emotion conveyance to human listeners in TTM systems using a dimensional valence-arousal framework. We constructed the dataset with 991 instrumental music clips from six TTM systems prompted with 12 emotion words spanning four valence-arousal quadrants. A total of 111 participants provided 6,162 valence and arousal ratings using a 9-point scale. The results revealed that all systems perform above chance in conveying quadrant-level emotion intent, yet overall accuracy remains limited. Notably, substantial model-dependent biases were present. Commercial systems tended to exhibit positive valence deviations, whereas open-source models more often produced outputs with a negative valence shift, with diverging arousal shifts. Furthermore, overall audio quality (Fréchet Audio Distance (FAD)) correlates with both valence and arousal, while text-audio alignment (Contrastive Language-Audio Pretraining (CLAP) score) primarily relates to valence. These findings highlight underlying challenges in conveying linguistic emotional semantics precisely through musically conveyed affect for future research on controllable and perceptually consistent music generation.
This study addresses a fundamental question in music psychology: which specific, dynamic acoustic features predict human listeners' emotional responses along the dimensions of valence and arousal. Our primary objective was to develop and validate an interpretable computational model that can serve as a tool for testing and advancing theories of music cognition. Using the publicly available DEAM dataset, containing 1,802 music excerpts with continuous valence-arousal ratings, we developed a novel, theory-guided neural network. This proposed model integrates a convolutional pathway for local spectral analysis with a Transformer pathway for capturing long-range temporal dependencies. Critically, its learning process is constrained by established principles from music psychology to enhance its plausibility. A core finding from an analysis of the model's attention mechanisms was that distinct acoustic patterns drive the two emotional dimensions: rhythmic regularity and spectral flux emerged as strong predictors of arousal, whereas harmonic complexity and musical mode were key predictors of valence. To validate our analytical tool, we confirmed that the model significantly outperformed standard baselines in predictive accuracy, achieving a Concordance Correlation Coefficient (CCC) of 0.67 for valence and 0.73 for arousal. Furthermore, an ablation study demonstrated that the theory-guided constraints were essential for this superior performance. Together, these findings provide robust computational evidence for the distinct roles of temporal and spectral features in shaping emotional perception. This work demonstrates the utility of interpretable machine learning as a powerful methodology for testing and refining psychological theories of music and emotion.
Although it is widely accepted that the First Old Church Slavonic Life of Wenceslas (FSL) is a tenth-century Bohemian composition written in Old Church Slavonic (OCS), some scholars have hypothesized a Latin original and subsequent translation. This article evaluates that hypothesis by testing the FSL against features typically associated with Latin-to-OCS translation, including loanwords, hendiadys, and morphological patterns. It argues that the FSL lacks consistent evidence of translation from a Latin source. While most Latinisms attested in the text are more plausibly explained as the result of cultural and religious contact with communities under Roman jurisdiction, even those expressions that appear more suggestive fail to meet the criteria of reliable translation markers and are better interpreted as scribal interpolations introduced during the text’s exceptionally complex transmission. Similarly, the purported instances of hendiadys and Bohemian morphological features are too sporadic and contextually ambiguous to support the hypothesis of a Latin prototext. Cases of quasi-hendiadic synonymic reinforcement are more likely to reflect broader literary conventions, and what has been interpreted as Bohemization may instead result from local linguistic norms affecting the text at later stages of its transmission. The article therefore concludes that the FSL should be regarded as an original OCS composition with an unusually complex transmission history.
This study empirically analyzed the error-processing patterns of five Korean grammar correction tools (Naver, Daum, Bareun-Hangeul, Gemini 3, and ChatGPT 5.2) currently utilized in the writing environment as of 2026. The findings revealed that while conventional rule- and statistics-based systems were effective for orthographic corrections, they exhibited a technical plateau in deep sentence-level error processing. In contrast, Gemini 3, a Generative Large Language Model (LLM), demonstrated superior contextual understanding and sentence restructuring capabilities, achieving an accuracy rate exceeding 90% across all domains. However, beneath this performance leap, a new form of “technical deceptiveness”—characterized by grammatical hallucinations and post-hoc rationalizations where incorrect corrections are fluently justified—was identified. Based on these results, this study first proposes “Critical AI Literacy” education, which enables learners to understand the probabilistic nature of generative AI and question the authenticity of its suggestions. Second, it suggests a “Writer-led Verification Process” as a core direction for literacy education in the AI era, empowering writers to make final judgments by cross-referencing AI-generated texts with linguistic norms rather than being subordinated to technical convenience. This research holds pedagogical significance by providing an empirical foundation for learner-centered critical writing education through a comprehensive examination of the possibilities and limitations of LLMs.
This research paper analyze error phrases in Instagram captions, focusing on the syntactic structures used by public figures. With the rise of social media, particularly Instagram, the language employed in captions has become a significant aspect of communication, influencing followers and shaping linguistic norms. The study aims to identify common syntactic errors in captions written in English, especially by non-native speakers. Utilizing a qualitative descriptive method, data were collected from 30 Instagram captions of verified public figures with over 100,000 followers. The analysis revealed five types of phrases: noun phrases (NP), verb phrases (VP), adjective phrases (AdjP), adverb phrases (AdvP), and prepositional phrases (PP). The researcher found that there are eighteen noun phrase, verb phrase appeared in five, adjective phrase appeared in six, and prepositional phrase appeared in one. Among these, noun phrases were the most prevalent, highlighting the need for awareness regarding grammatical accuracy in social media communication. The findings suggest that public figures should be more cautious with their language use, as errors can mislead their audience and perpetuate incorrect language forms. This research contributes to the understanding of language use in digital contexts and offers recommendations for improving caption writing among social media users.Keywords: Syntax, Error phrase, Types of phrases, Instagram caption, Public figure.
In the field of natural language processing (NLP), accurate alignment of text units in a parallel corpus is important for tasks such as machine translation, cross-lingual information retrieval, and bilingual lexicon creation. However, identifying simple sentences and correctly assigning their types poses certain difficulties during the alignment process, especially at the paragraph and sentence levels. This article analyzes the problems encountered in identifying and matching simple sentences and their structural differences. Factors such as syntactic differences, sentence splitting or merging, and language-specific sentence structure increase the complexity of this process. The study considers problematic situations that arise during the alignment process, proposes criteria for determining the type of simple sentences, and describes the aligning process using a rule-based method to increase the accuracy and consistency of aligning, and provides a linguistic database. The results obtained serve to improve multilingual NLP systems by improving the quality of corpus-based language resources.
Inspired by general deviance theory, which proposes that individual traits predispose people to violate multiple types of norms or rules, we suggest that disregard for native language rules of speech may be positively correlated with disregard for other social norms such as truth-telling. Specifically, we hypothesize that given the opportunity to gain financially through untruthful statements, native-born speakers who speak incorrectly will be more likely to exploit it than their counterparts who speak correctly. We report the results of testing this hypothesis on Israeli students, using two double-stage experiments. The first stage, identical in both experiments, was intended to identify untruthful statements by applying the popular die-under-the-cup task. The second stage, aimed at identifying incorrect pronunciation, differed between the two experiments. In the first experiment, participants were asked to read aloud 10 sentences, whereas in the second experiment, conducted in writing, participants were presented with the same 10 sentences, this time phrased as questions with multiple-choice answers regarding the correct pronunciation. Our hypothesis that untruthful statements are positively correlated with incorrect speech was confirmed in both experiments, thereby providing empirical support for the notion that linguistic norm violations may extend beyond the domain of grammar and be linked to broader patterns of social norm disregard, such as truth-telling.
Le French Treebank: une ressource lexicale et syntaxique richement annotée (et validée manuellement) pour les linguistes, utilisable en TAL, dans sa version 2.0 Projet initié en 1997, avec le soutien de l'IUF, du CNRS et du CNRTL21 550 phrases (environ 664 500 tokens) du journal Le Monde (1990-1993)Métadonnées: auteur, date, domaine (par article)Annotations lexicales (catégories, sous-catégories, flexion, mots composés avec composants) et syntaxiques (constituants majeurs, fonctions grammaticales) validéesPlusieurs formats disponibles: XML, PTB, CoNLL, codage UTF-8 (ligature œ notée oe)Nouveautés de la version 2.0: plusieurs erreurs d'annotation ont été corrigées depuis la publication en 2016 de la version 1.0
Contemporary large language models (LLMs) rely on sub-word tokenizers and at attention mechanisms that treat every language as a statistical surface-form distribution. This paper proposes Dhatu-Former, a transformer architecture that internalizes the formal linguistic machinery of Pan.ini’s As..tadhyay the oldest known generative grammar. We hypothesize that (i) morphologically-aware, root-based (dhatu-based) tokenization can reduce vocabulary size and sequence length by 40 60%, (ii) hierarchical attention guided by Pan.inian derivation trees can yield sparse, interpretable attention with O(nlogn) complexity, and (iii) a hybrid symbolic neural reasoning layer that executes sutra-style rewrite rules can substantially reduce hallucination while enabling uni ed language math logic reasoning. We further introduce a modular Retrieval-Augmented Generation (RAG) subsystem grounded in Sanskrit lexical databases (Amarakos.a, Dhatupat.ha) and a continual learning framework inspired by the paribhas.a sutra (meta-rules) of the As..tadhyay. We present order-of-magnitude parameter reduction estimates, architectural blueprints with TikZ diagrams, and a research roadmap for empirical validation. This is a position paper; no experiments have been conducted.
The Arabic neologism Aranjiyya (عَرَنْجِيَّة) is a portmanteau of ʿArabiyya (Arabic) and Inkliziyya / Faranjiyya (English/foreign), used by contemporary Arabic editors and stylists to describe Arabic prose that retains Arabic vocabulary while importing the syntactic, stylistic, semantic, or lexical structures of English. The phenomenon is pervasive in translated news, press releases, technical writing, and digital media, and is a recurrent target of prescriptive Arabic-style guides. Despite its prominence, Aranjiyya has had almost no presence in computational Arabic resources: existing treebanks and error corpora target orthographic, morphological, or syntactic well-formedness but do not isolate contact-induced patterns whose surface forms are grammatical but whose underlying templates are English. AranjiyyaCorpus was constructed to fill this gap, with three motivating use cases: training a span-level Aranjiyya detector for editors and translation post-editors; producing evaluation data for whether large language models actually generate idiomatic Arabic; and supporting linguistic study of contact-induced change in modern Arabic, with sufficient category granularity to distinguish syntactic, stylistic, and semantic phenomena and to track them across genres.
BACKGROUND: Atypical reward responsiveness is crucial for the onset and maintenance of non-suicidal self-injury (NSSI). There is no consensus whether NSSI is associated with increased or decreased reward responsiveness, due to different reward modalities, stages of reward processing examined, and the confounding effects of psychiatric comorbidities. This study aims to investigate reward responsiveness across different reward modalities—monetary and emotional—as well as distinct phases of reward processing, namely anticipatory and consummatory stages, among adolescents with NSSI. METHODS: The monetary and affective incentive delay (MID & AID) tasks were utilized to compare anticipatory and consummatory emotions as indicated by self-reported valence ratings between adolescents with NSSI (n = 103) and controls (n = 94) via ANOVA. The NSSI group was further separated into the NSSI + Suicidal Attempt (SA) and NSSI-only subgroups to examine whether NSSI co-occurring with suicidal behaviors resulted in more severe reward abnormalities. Sensitivity analyses using ANCOVA and hierarchical regression controlled for anhedonia symptoms to test the specificity of associations with NSSI. RESULTS: Adolescents with NSSI reported lower positive emotions when anticipating rewards, and experienced less pleasure after winning rewards or avoiding punishment. The NSSI + SA subgroup, compared with NSSI-only adolescents, had less consummatory pleasure in the MID task. However, blunted reward responsiveness in NSSI was no longer significant after controlling for anhedonia symptoms. CONCLUSIONS: NSSI is correlated with blunted reward responsiveness, primarily confounded by depressive symptoms (especially anhedonia). Co-occurring NSSI and SA is a more severe form of self-harm.
Memory cues can be associated with both positive and negative experiences at different time points, in either a positive-to-negative or negative-to-positive order. While sleep preferentially consolidates recent experiences, its impact on emotional memory across such opposing-valence sequences remains unclear. We tested whether sleep differentially modulates delayed cue affect in positive-to-negative versus negative-to-positive conditions. One hundred twenty participants were randomly assigned to sleep or wake groups and completed both conditions in counterbalanced order. Participants learned pseudoword-picture associations where the same cues were paired with emotional pictures of opposite valence. Emotional valence ratings were collected immediately after encoding and after a 12 h interval (overnight sleep vs. daytime wakefulness). Sleep led to more positive cue ratings in the negative-to-positive condition and more negative ratings in the positive-to-negative condition, compared to wake controls. Stronger positive picture ratings predicted greater positive-valence shifts after sleep in the negative-to-positive condition. These findings indicate that sleep preferentially modulates the affective tone of memories encoded closer to sleep onset, independent of recognition accuracy. This suggests a dissociation between mnemonic and affective consolidation, where sleep selectively biases emotional value according to the temporal order of experience. This principle may inform therapeutic strategies for optimizing emotional outcomes by timing positive experiences before sleep, though clinical applications require further study.
Introduction Aging is associated with reduced accuracy in recognizing others’ emotions, an ability that is important for maintaining social connectedness in later life. Laughter is a social signal with multiple functions, as it can facilitate social bonding but also convey negative social meanings, for example when directed at someone. In previous research we have shown that younger adults are able to classify spontaneously emitted joyful, schadenfreude, and tickling laughter above chance level, and that these laughter sounds differ according to the perceived dominance. Given evidence that affect recognition generally declines with age, the present study examined whether comparable age effects emerge in the perception of laughter. Methods 64 younger adults (mean 25 years, 18–33 years) and 30 older adults (mean age 60 years, 50–77 years) evaluated 117 spontaneously emitted laughter sounds according to the laughter type, i.e., joyful, Schadenfreude, and tickling laughter and according to the perceived sender’s dominance. Results Results showed that both age groups classified laughter above chance level. Younger adults showed higher classification rates than older adults for all laughter types, with the largest age effect for Schadenfreude laughter. The dominance ratings showed an age effect only for Schadenfreude, where older adults rated Schadenfreude laughter less dominant than younger adults. Discussion Pronounced differences in Schadenfreude perception might be ascribed to difficulties of older adults in perceiving non-literal messages or to cultural differences between age groups.
Abstract The linguistic study of the divine names in votive inscriptions has recently attracted increasing interest. In this paper, the author discusses phonetic changes in Latin names and epithets of gods using data from the Computerized Historical Linguistic Database of Latin Inscriptions of the Imperial Age. The vowel and consonant changes in votive inscriptions across the Roman Empire are in the focus and certain Vulgar Latin features and cultural influences can be identified from the corpus. The study focuses on common phonetic phenomena, such as vowel and consonant changes, monophthongization, gemination, etc. The epigraphic corpus shows various Vulgar Latin features in theonyms and epithets, which are considered linguistic, regional, and cultural factors that influenced these changes, including Celtic, Greek, and Brittonic influences. The research concludes that the observed phonetic variations reflect the dynamics of the development of Latin as well as language contact phenomena affecting it.
Background: Word identification in noise is crucial for effective communication in everyday environments. For children, the ability to identify words in noisy conditions directly impacts language development, learning, and social interaction. This study aimed to develop and standardize Hindi word identification in noise test for children (HWINT-C) and evaluate its performance among school aged typically developing children across varying SNR and word length. Methods: The study included forty two participants which were further subdivided into subgroup one consisting of 22 typically developing children aged 6-7.11 years (SGI) and 20 typically developing children aged 8-10 years in subgroup two (SGII). Development of Hindi word identification in noise test for children (HWINT-C) involved multi-step processes including selection of words, familiarity rating, and content validation, internal consistency and test-retest reliability. The test included bisyllabic and monosyllabic words recorded by a native Hindi female speaker presented in eight-talker babble at +5 dB and +7 dB SNR administered dioticallyat 65 dB SPL. Results: The developed HWINT-C in this study demonstrated to have high internal consistency and test-retest reliability. Typically developing children in the older group (SGII) significantly outperformed the younger group (SGI), Additionally performance improved with increasing signal-to-noise ratio (SNR) in both SGI and SGII, but no significant differences were found across word lengths. Conclusions: The HWINT-C test is a reliable and valid tool for assessing word-in-noise perception in children. Age-related trend was observed, where performance improved with age, Similar findings were observed with increase in SNR, emphasizing need of favorable conditions in younger population.
в статье представлено исследование, посвящённое сопоставлению подходов к обучению иностранному языку студентов направления «Зарубежное регионоведение». Предмет анализа связан не просто с овладением языковой нормой иностранной речи, а с формированием такой модели речевой подготовки, при которой студент способен соотносить высказывание с конкретным регионом, его политико-культурной спецификой, медийной повесткой и типичными коммуникативными сценариями. С помощью методов анализа, синтеза, наблюдения и описания произведено рассмотрение актуальных на данном этапе развития высшего образования способов формирования иноязычной региональной компетенции. С позиции компетентностного и деятельностного подходов обучение рассматривается как движение от языковой операции к регионально маркированному высказыванию, которое строится в ситуации обсуждения, аргументации, интерпретации и переговоров. Сложный характер данной компетенции требует использования в процессе преподавания разнообразных методов активного и интерактивного обучения, инновационных образовательных технологий, форм и средств обучения, тесно связанных с будущей профессиональной деятельностью студентов направления подготовки «Зарубежное регионоведение». this article presents a study comparing approaches to foreign language instruction for students majoring in “Foreign Regional Studies”. The subject of analysis is not merely the mastery of the linguistic norms of Chinese speech, but the development of a model of language training in which students are able to relate a statement to a specific region, its political and cultural characteristics, media agenda, and typical communicative scenarios. Using methods of analysis, synthesis, observation, and description, this study examines the methods of developing foreign language regional competence that are relevant at this stage of higher education development. From the perspective of competence-based and activity-based approaches, teaching is viewed as a progression from linguistic operations to region-specific utterances, which are constructed in situations of discussion, argumentation, interpretation, and negotiation. The complex nature of this competence requires the use in the teaching process of a variety of active and interactive teaching methods, innovative educational technologies, and forms and means of instruction closely linked to the future professional activities of students training program "Foreign Regional Studies".
This repository contains GSD-NP and GSD-DiNoS, both derived from Universal Dependencies' (UD) GSD Treebank. GSD-NP (.conllu) is a subset of UD-GSD and comprises its simplex noun phrases (NP): Common nouns (NN/NOUN) and their direct dependents (determiners, adnominal adjectives, nmods, adpositions, adverbs). It consists of 49,425 NPs (119.0k tokens) and has an improved feature annotation coverage (gender, case, number). Breaking with UD annotation, a total of 3,649 APPRART tokens were reconstructed in GSD-NP to restore the original orthographic forms. GSD-DiNoS (.json) is a custom data-driven lexion-like data structure built on GSD-NP, which aggregates NPs with the same head lemma. For each lemma, absolute frequencies of the lemma and its word forms are captured. Moreover, each occurrence feeds into three areas of interest within the word form entry: morphosyntactic features in isolation (gender, case, number), in combination with groups of dependents (collocations), and in combination with the syntactic function (dependency relations). GSD-DiNoS spans 17,433 unique lemmas and 20,190 unique word forms, stemming from 49,416 NPs. Lemmas were relemmatised to assign unique lemmas to nominal compounds, a highly productive and often lexicalised construction in German.
This article examines the transformation of professional training for future English language teachers amid the rapid development of artificial intelligence (AI) technologies. The integration of generative tools into the educational environment creates not only new didactic opportunities but also significant methodological and ethical challenges, the most critical of which is the reliability of AI-generated content. Current educational programs tend to focus primarily on the instrumental use of technology, while methodologies for developing critical-analytical skills remain underdeveloped. The aim of the study is to theoretically substantiate and empirically test a methodology for developing the verification skill of AI-generated responses during language tasks. The paper clarifies the concept of "verification skill", defining it as an integrated professional ability to analyse, evaluate, and correct AI outputs in accordance with linguistic norms and methodological soundness. A structure for this skill is proposed, comprising four interconnected components: cognitive (knowledge of AI principles), analytical-evaluative (error detection), operational-corrective (editing), and value-reflexive (academic integrity). Based on empirical data collected from students of the Philological Faculty, the level of development of this skill was analysed. The results indicated that future teachers mostly possess fragmented abilities in editing AI texts: the cognitive component is the most developed, whereas the operational-corrective component is the weakest due to the unsystematic nature of corrections. It was also found that students tend to focus on formal accuracy while neglecting stylistic and methodological nuances. The study concludes that purposeful implementation of verification methodology in professional training is essential to ensure teachers’ methodological autonomy in a digitized environment.
The online review of veterinary services, as a new format of interaction between the client and the veterinarian, represents a value-oriented genre of veterinary discourse, characterized by variability in structure and volume. The high degree of emotionality and expressiveness indicates a strong positive bond between human and animal. This study fits into the framework of an innovative interdisciplinary approach to the concept of zooesis. The article aims to describe the linguistic means of expressing evaluation in an online review as a new genre of veterinary discourse and to determine the prospects for research. The study employed general scientific analysis methods, descriptive methods, and componential analysis. We analyzed 500 customer reviews of UK veterinary service providers posted on the clinics’ official websites. We found that the primary means of expressing evaluation is evaluative vocabulary, phraseology, and expressive syntax, while nonverbal emotional cues are used to a lesser extent. It has been demonstrated that the arbitrariness of the subject’s choice of linguistic means leads to the violation of linguistic norms which brings online veterinary reviews closer to colloquial speech. It has also been established that the majority of reviews (93%) are melioration-oriented. The linguopragmatic properties of linguistic means of expressing assessment in an online review of veterinary discourse are determined as a factor ensuring the success of distance communication, influencing the image and reputation of a veterinary institution. The results of this study can be used in university courses on communication in veterinary medicine and veterinary ethics. Prospects for future research include comparative stylistic studies of the online review genre and other genres of Internet content, and comparative analysis of online reviews.
The article analyzes the influence of economic factors on the language attitudes of youth. According to the theory of P. Bourdieu, the dominance of linguistic norms and forms is viewed as a factor that exacerbates social inequality. Proficiency in different languages increases an individual's social capital and expands their economic opportunities, while language barriers restrict access to these resources. The language choice among young people is largely determined by their economic status. It is posited that income levels facilitate the learning of foreign languages, whereas, in conditions of social inequality, the ability of youth to maintain their native language is taken into account. The study examines the impact of economic factors–such as labor market requirements, educational opportunities, and income levels–on multilingualism and language choice among the younger generation. The research provides insight into how economic drivers influence language choice, language policy, and the acceptance of multilingualism in society. The author presents the results of applied research based on the focus group method. Focus groups were conducted across 12 regions (N=167). According to the results, language choice among youth depends on regional and ethno-demographic characteristics. Furthermore, the global economy and globalization trends push young people toward learning multiple languages, while disparities between urban and rural areas also affect language attitudes. While youth with high-income levels strive for multilingualism, low-income groups prioritize their native language. The findings of this study play a crucial role in forming effective state and educational language policies that can enhance the success of young people in social and professional life.
The article examines lacunarity as a linguistic, semantic, and linguocultural phenomenon manifested in asymmetries between languages at the lexical, grammatical, phraseological, and pragmatic levels. The study aims to clarify the theoretical status of lacunarity in modern linguistics and to show how lacunar relations operate in contrastive analysis, translation, lexicography, and intercultural communication. The research is based on descriptive, comparative, and interpretive methods and synthesizes findings from lexical semantics, translation studies, and multilingual lexical database research. The analysis demonstrates that lacunarity should not be reduced to the simple absence of a word in one language. Rather, it reflects deeper mismatches in conceptual segmentation, communicative priorities, cultural salience, and grammatical encoding. Particular attention is paid to the distinction between lexical gaps and referential gaps, to specification and generalization mismatches, and to the problem of equivalence in translation. The article argues that lacunarity is not a defect of language but a normal consequence of the selective way in which languages lexicalize experience. It is further shown that lacunarity has methodological value: it reveals culturally marked concepts, tests the limits of bilingual equivalence, and exposes the need for explanatory, contextual, and compensatory strategies in translation and lexicography. The conclusion states that lacunarity is one of the most productive analytical categories for understanding how linguistic systems differ while remaining mutually interpretable in discourse.
When stimuli are retained in visual working memory (VWM) external stimuli which overlap with this representation capture attention when performing a visual task. It has not been determined, however, whether this mechanism can partly account for attentional capture by categories of real-world affective stimuli. Across five dual-task visual search and VWM change detection experiments (4/5 pre-registered; total N = 119) participants had to detect the change in either positive (kitten) or threat-related (spider) animal exemplars, whilst performing an intervening visual search task with peripheral distractors from these affective categories. The affective stimulus associations were confirmed by arousal and valence ratings in all five samples and in an independent sample (n = 82). It was hypothesised that threat-related and positive distractors would capture attention more, versus a neutral (bird or no distractor) baseline, when matching the contents of VWM. Experiments 1-3, however, found no evidence of increased capture by VWM-matching affective stimuli, though there was cumulative evidence of goal-independent capture by threat-related distractors. When, however, the trial structure became unpredictable, requiring constant preparation for the VWM task response (Experiment 4), or advanced action preparation to the VWM task was enabled (Experiment 5), then VWM-matching threat-related distractors caused greater attentional capture. This VWM-driven capture, however, was not found for positive distractors in any experiments. The results probe the boundary conditions when VWM contents drive attentional capture by entirely task-irrelevant affective categories, and suggests that background memory representations may not influence attention unconditionally, and instead may depend partly on their current prioritisation.
Emotion recognition plays a crucial role in human–computer interaction, health monitoring, and affective computing by analysing physiological signals. Despite recent advancements, current research still faces challenges, including the lack of effective fusion strategies for diverse physiological modalities, difficulties in handling high-dimensional feature representations, and limited use of efficient temporal modelling techniques to capture complex emotional patterns. This study proposes a deep learning-based approach that fuses multiple physiological modalities, including Electroencephalography (EEG), Electrooculography (EOG), Electromyography (EMG), Galvanic Skin Response (GSR), Respiratory Rate (RR), Skin Temperature (SKT), and Photoplethysmography (PPG), to improve emotion recognition. Arousal and valence ratings were binarized into two classes (low/high) using a threshold of 4.5, formulating a binary classification problem. In addition to utilising Bidirectional Long Short-Term Memory (Bi-LSTM), the study employs Temporal Convolutional Networks (TCN), a widely used approach for time-series analysis, to efficiently capture temporal dependencies. The proposed model optimises feature selection through channel-wise strategies, incorporates advanced learning rate scheduling, and reduces computational overhead. Furthermore, window-wise, block-wise, and trial-wise evaluation protocols were investigated to assess the impact of temporal information leakage on emotion recognition performance. Using the DEAP dataset for validation, the proposed TCN-based approach achieved classification accuracies of 88.42% for valence and 86.35% for arousal under an overlapping block-wise evaluation protocol, demonstrating improved performance in binary emotion recognition and highlighting the importance of leakage-aware model assessment.
Recent advances in Large Reasoning Models (LRMs), particularly those leveraging Chain-of-Thought reasoning (CoT), have opened brand new possibility for Machine Translation (MT). This position paper argues that LRMs substantially transformed traditional neural MT as well as LLMs-based MT paradigms by reframing translation as a dynamic reasoning task that requires contextual, cultural, and linguistic understanding and reasoning. We identify three foundational shifts: 1) contextual coherence, where LRMs resolve ambiguities and preserve discourse structure through explicit reasoning over cross-sentence and complex context or even lack of context; 2) cultural intentionality, enabling models to adapt outputs by inferring speaker intent, audience expectations, and socio-linguistic norms; 3) self-reflection, LRMs can perform self-reflection during the inference time to correct the potential errors in translation especially extremely noisy cases, showing better robustness compared to simply mapping X->Y translation. We explore various scenarios in translation including stylized translation, document-level translation and multimodal translation by showcasing empirical examples that demonstrate the superiority of LRMs in translation. We also identify several interesting phenomenons for LRMs for MT including auto-pivot translation as well as the critical challenges such as over-localisation in translation and inference efficiency. In conclusion, we think that LRMs redefine translation systems not merely as text converters but as multilingual cognitive agents capable of reasoning about meaning beyond the text. This paradigm shift reminds us to think of problems in translation beyond traditional translation scenarios in a much broader context with LRMs - what we can achieve on top of it.
The limitless semantic potencies of communication is within the framework of the language conventional semantics, which imposes a number of restrictions, including on the explication of emotional experiences by the speaker. The latter either chooses a read y-made preset formula, or directs communicative efforts to search for and objectify emotional and semantic shades of meaning with an uncodified form of verbalization. If the form of expression of an emotional experience is new, atypical, unconventional, we should talk about the representation of diffuse emotive semantics, approaching the actual emotional experience. Diffusivity (fuzziness, vagueness, multiple inconsistencies, ambiguity) is an immanent property of semantics that corresponds to both the natur e of the sign and the environment in which the sign acts. The assumption is that, depending on the characteristics of the discourse and the genre characteristics of the elements included in it, artistic communication was considered. The author of a work of art must go beyond the linguistic prescription, which allows him to have the desired effect on the addressee. The analysis of a dramatic work shows a variety of forms of explication of diffuse emotivity, when emotional experiences become a discursive and genre-forming category: the expression of complex vague emotions allows creating an image of a multifaceted and interesting character. The texts of modern plays allow tracing a similar trend towards diversifying the form of expression of diffuse emotivity, but the emotional tonality is less diverse: negative emotional experiences set the emotional dominant, therefore, the ‘consolidation’ of the emotive occurs rather than through the vector of mixing positive and negative assessments, but the intensification and concretization of the negative evaluative component. The author also postulates that language always approximately describes emotions, but in artistic communication such approximativeness is expressed in conscious and creative imitation, which transforms and develops the linguistic norm.
This study examines the current state and future prospects of Urdu digital translation within the broader historical and technological development of machine translation. It begins by outlining the evolution of digital translation systems and reviewing their application across major world languages, followed by a critical analysis of existing Urdu translation platforms such as Google Translate, Bing Translate, ChatGPT, and other AI-based tools. The research identifies key linguistic and technical challenges that affect Urdu translation quality, including script directionality, morphological and syntactic complexity, polysemy, idiomatic expressions, cultural references, tokenization and parsing difficulties, and Unicode compatibility issues. By situating Urdu within the framework of Artificial Intelligence (AI) and Natural Language Processing (NLP), the study highlights the need for language-specific AI models, large-scale corpora, annotated treebanks, and domain-sensitive lexical resources to improve translation accuracy and contextual coherence. It further explores the applicability of advanced language models such as BERT, LLaMA, and generative AI systems in enhancing Urdu machine translation. In response to the identified limitations, the research proposes a corpus-driven, AI-integrated Urdu translation web application framework designed to provide context-aware, stylistically appropriate, and semantically accurate translations. The study contributes both analytically and practically by offering a comprehensive evaluation of Urdu digital translation and presenting a scalable model aimed at strengthening Urdu’s position in the global digital and AI-driven linguistic landscape.
We present a large-scale evaluation of the Menzerath-Altmann law (MAL) in the verbal domain across 180 languages, using the Universal Dependencies (UD) treebank collection (v2.17).MAL predicts that as the number of constituents of a linguistic unit increases, their average size decreases.We propose a metric to estimate the MAL effect across corpora of widely varying sizes and define threshold-based categories to classify languages along a MAL preference cline.Crucially, we analyse the preverbal and postverbal domains separately, in addition to the standard bilateral MAL, and control for potential sampling bias by comparing results across language families (Indo-European vs. non-Indo-European) and syntactic types (VO, OV and no dominant order).Our results confirm MAL as a typologically widespread preference but not an absolute universal: several languages display a trivial or even opposite (anti-MAL) tendency.Furthermore, we uncover a significant asymmetry between the two sides of the verb: the MAL effect is stronger in the postverbal domain, while anti-MAL is stronger in the preverbal domain.VO languages tend to show a stronger MAL preference postverbally, whereas OV languages do so preverbally.These findings challenge the widespread assumption that length-based ordering constraints apply symmetrically on both sides of the verb and contribute new cross-linguistic evidence to the debate on the interaction between dependency length minimization and constituent size.
TIn Lithuania, inclusive education is legally embedded in the Law on Education and its 2020 amendments, which guarantee children with disabilities the right to attend mainstream schools on an equal basis and ensure access to necessary support and non-discrimination. The law also provides Deaf pupils with a formal opportunity to learn Lithuanian Sign Language. At the international level, inclusive education is closely linked to human rights, equality, and social justice. The United Nations Convention on the Rights of Persons with Disabilities (CRPD) and the World Federation of the Deaf (WFD) emphasise the right of Deaf people, as a linguistic and cultural minority, to full and meaningful participation in education. This paper presents the results of qualitative research exploring how adult Deaf individuals retrospectively interpret and make sense of their experiences in mainstream schooling in Lithuania. The study seeks to illuminate the complex reality of deaf education, where linguistic and cultural dimensions intersect within the framework of inclusive education. The literature review draws on transformative equality theory, arguing that inclusive education requires not only formal access but structural transformation of linguistic norms, cultural recognition, and participatory frameworks within mainstream schooling. Particular attention is given to the linguistic and cultural dimensions of Deaf identity within this equality paradigm. The research is based on semi-structured interviews with adult Deaf participants and employs interpretativephenomenologicalanalysis(IPA).The findings reveal that mainstream schooling was frequently experienced as isolating and implicitly segregating, while Lithuanian Sign Language emerged as a crucial condition for recognition, belonging, and participation. The study suggests that inclusive education for Deaf learners requires transformative structural change grounded in principles of equality to ensure linguistic rights and cultural recognition.
ABSTRACT Classical fear conditioning describes how neutral cues acquire a threat value, yet how learned associations are retrieved and generalised across similar stimuli specifically is an ongoing debate. We combined behavioural ratings, physiological measures, and fMRI in a two-day classical fear conditioning paradigm to characterize acquisition, retrieval, and generalisation across modalities. Twenty-five healthy participants completed acquisition trials on Day 1 and retrieval and generalisation trials on Day 2 using conditioned (CS+, CS-) and graded generalisation stimuli (GS). Outcomes included trial-wise US expectancy ratings, pre/post fear and arousal ratings, skin conductance responses (SCR), pupil dilation, and ROI-based fMRI (amygdala, hippocampus, insula, periaqueductal gray (PAG), locus coeruleus). Acquisition yielded robust CS+/CS-discrimination in behavioural ratings and increased BOLD responses in bilateral insula and PAG. During retrieval, US-expectancy ratings indicated early retrieval of CS contingency. The fMRI results showed greater BOLD activity during CS+ presentations than during CS-presentations in bilateral hippocampus, left insula and right PAG. Additionally, hippocampus-insula coupling increased. Critically, parametric modulation during retrieval revealed that trial-wise mean US-expectancy modulated BOLD responses in left insula and right PAG, with a trend in left hippocampus. Across generalisation, US-expectancy and pupil dilation responses followed graded profiles, which could be explained by a Gaussian model, whereas SCR generalised, but was not captured by a Gaussian model. Parametric modulation by US-expectancy correlated with BOLD activity in left PAG, with a trend in right hippocampus. Stimulus identity explained variance in bilateral insula and left PAG. Findings converge on a hippocampus-insula-PAG network that retrieves learned predictions, and scales defensive output according to similarity-based threat probability, linking subjective, physiological, and neural outcomes.
Introduction. The article is devoted to the analysis of nominations referring to persons with disabilities in the modern German language. The aim of the study was to identify the main structural features of these nominations, their semantics and functioning across various discourse types. The scientific novelty of the work lies in the integrated approach to the study of nominations, combining linguistic and socially oriented parameters of analysis. The relevance of the study is due to the growing attention of society to issues of inclusion and the need to form a correct linguistic norm regarding the designation of persons with disabilities. Methodology and sources. The methodological framework of the study is the cognitive, pragmatic and sociolinguistic approaches, allowing to consider the nomination as a result of the interaction of language and social representations. The empirical basis of the study is German-language texts of medical, legal and media discourses. The data were collected through continuous sampling from six publications about people with disabilities. The analysis includes the systematisation of the identified designations, the determination of their discursive functions and their interpretation within contemporary linguistic practice. Results and discussion. The total number of extracted nominations was 209 units. The obtained results show that the analysed texts are dominated by neutral and inclusive nominations aimed at emphasising the individual rather than his/her health problems. Legal texts are dominated by nominations established by law, reflecting the legal status of persons with disabilities. Medical texts demonstrate a high level of detail in describing the disabilities of individuals, which is reflected in their designations. In media texts, a combination of neutral and evaluative nominations is observed, which is associated with the influence of social stereotypes and emotions. Conclusion. The obtained results indicate the formation of an inclusive norm in the German language, focused on respectful and neutral designation of disability. Nominations serve as an important tool for representing individuals and reflect dynamic changes in society.
Abstract Building syntactically annotated corpora, such as treebanks, for historical languages is a challenging yet vital task in digital humanities, as it underpins linguistic analysis and facilitates a range of interdisciplinary research. However, the scarcity of annotated data and the need for extensive expertise in historical linguistics make this process particularly demanding. In this study, we explore the potential of cross-lingual natural language processing (NLP) techniques as a semiautomatic solution for treebank construction in low-resource historical languages. We use Middle High German (MHG) as a case study. Leveraging the linguistic continuity and structural similarities between MHG and Modern German (MG), we effectively utilize the extensive MG treebank resources to develop a constituency parsing system tailored for MHG. Specifically, to design a semiautomatic system that integrates automatic annotation with manual validation, we explore two cross-lingual transfer techniques: zero-shot transfer and delexicalization; the latter removes lexical information to focus on syntactic structure. In our experiments, we first train parsers on MG treebanks, and then transfer them to MHG using the two cross-lingual transfer techniques. The delexicalization method achieves a parsing performance of 67.3 per cent in terms of F1-score. This performance significantly surpasses the zero-shot cross-lingual method by a margin of 28.6 percentage points. These investigations validate the effectiveness and feasibility of cross-lingual transfer techniques for historical language treebank construction. This study highlights the potential of NLP tools to streamline the semiautomatic annotation process, reducing the reliance on extensive linguistic expertise and manual effort, and paving the way for broader applications in digital humanities research.
BACKGROUND: Psychopathic characteristics are associated with an elevated risk for violent behavior and are therefore of interest in research studies. Despite extensive research, the role of emotional and attentional anomalies in subclinical psychopathic traits remains a subject of ongoing debate, possibly attributed to the multifaceted nature of the construct. The study aims to explore how distinct psychopathic traits may differently relate to underlying emotional and attentional mechanisms. METHODS: To further explore the emotional and attentional anomalies underpinning the three Triarchic Psychopathy constructs, boldness, meanness, and disinhibition, this study employed an optimized picture-startle paradigm to address the limitations in commonly used paradigms that capture these dynamics only after 1000 ms post-image onset. This paradigm included negative, positive, and neutral images to elicit varied emotional responses, while auditory startle probes were presented at 50, 700, or 4500 ms post-image onset to measure emotional and attentional fluctuations. In this study, it was proposed that each psychopathic trait correlates with distinct emotional and attentional anomalies. A mixed-gender community sample of 115 participants was included. Eyeblink startle amplitudes (ESAs) were recorded via smartphone technology that utilizes facial landmark data captured via phone cameras, while the P3a and late positive potential (LPP) were measured through electroencephalography (EEG). RESULTS: The results revealed an exaggerated attentional bottleneck associated with boldness in males, indicated by increased P3a amplitudes in response to negative images. Meanness was associated with lower empathy scores and arousal ratings, and reduced ESAs at 4500 ms for negative images, supporting socio-emotional difficulties in meanness. In contrast, disinhibition showed no significant emotional or attentional deviations in this study. CONCLUSIONS: Our findings highlight trait-specific differences in neurocognitive functioning and validate the effectiveness of the optimized picture-startle paradigm for dissociating attentional versus emotional anomalies across triarchic psychopathic traits. The study also demonstrates the feasibility of using BlinkLab’s integrated stimulus presentation and camera-based eyelid tracking with concurrent EEG measures of attentional and affective processing (P3a and LPP), providing a complementary approach that may facilitate scalable data collection.
Status: Working Paper This manuscript is a work in progress and represents a preliminary formulation of the Cognitive Alignment framework. The concepts and definitions herein are subject to further refinement and peer review. This working paper introduces Cognitive Alignment Theory, a framework challenging the "file transfer" model of communication in favor of a functionalist "remote control" model. I propose that true intersubjective understanding is impossible due to the Solipsistic Veil—the impenetrable barrier isolating individual qualia. Consequently, communication does not transmit internal states but functions as Wireless Tinkering: the use of linguistic signals to trigger simulated heuristics in the receiver's database. Success in this model is defined not by shared feeling, but by Cognitive Alignment: the synchronization of behavioral logic and output, regardless of internal divergence. This reliance on alignment over understanding creates the risk of Solipsistic Exclusion, where marginalized agents are structurally isolated because dominant linguistic databases lack the "hardware" to simulate their lived reality. Finally, I apply this framework to Large Language Models (LLMs), arguing that AI systems utilize "heuristic steering" to achieve Cognitive Alignment without possessing an internal reality, potentially leading to mass manipulation via personalized "wireless tinkering".
The article describes the principles of forming linguistic and communicative competence in future doctors during their studies at medical higher education institutions with a view to popularisation medical knowledge, and substantiates the content and structure of a special linguistic discipline in the Ukrainian language for popularisation medical knowledge. The regulatory documents of the Ministry of Health of Ukraine, which describe the qualification characteristics of professionals in the field of medicine and dentistry, emphasise the importance of the multifaceted activities of doctors in disseminating medical knowledge among the population. The current educational standard in the healthcare sector does not include a component that would promote the development of language skills for popularisation medical knowledge. Therefore, it is important to introduce the study of the peculiarities of the linguistic structure and production of relevant genres of popular scientific medical language into the curricula of higher medical education institutions. It is proposed to introduce a special component in one of the senior courses to develop future doctors’ linguistic and communicative competence in popularisation medical knowledge – the academic discipline ‘Ukrainian Language Popularisation of Medical Knowledge’. This discipline is intended for higher education students who have already studied several disciplines in the professional training cycle and have sufficient background knowledge to independently create high-quality popular science texts on the medical disciplines they have studied. As a result of studying the discipline, higher education students should know the terminology of popular science medical text creation, the genre structure of popular medical discourse, be able to create works in relevant genres of popular medical discourse, and master the linguistic norms of popular medical style. The possibility of introducing topics for the formation of linguistic and communicative competence in the popularisation of medical knowledge into the compulsory course of the Ukrainian language (for professional purposes) with the addition of credits in the fourth and fifth years of study is justified. The possibility of introducing a similar discipline for higher education students of various fields and specialities is indicated.
Annotatsiya. ushbu maqolada til va nutq dixotomiyasining zamonaviy tilshunoslikdagi talqini, lisoniy birliklarning nutqiy jarayonda voqealanish qonuniyatlari tadqiq etiladi. Maqolada tilning statik tizim sifatidagi tabiati va nutqning dinamik hodisa sifatidagi o‘ziga xosliklari qiyosiy tahlil qilingan. Shuningdek, fonema, morfema, va leksemalarning nutqiy zanjirda variantlashish xususiyatlari, lisoniy me’yor va nutqiy variativlik munosabatlari yoritib berilgan. Kalit so‘zlar: til, nutq, lison, voqealanish, lisoniy birlik, nutqiy birlik, paradigma, sintagma, variant, invariant, nutqiy faoliyat, til tizimi. Аннотация. В данной статье исследуется интерпретация дихотомии языка и речи в современной лингвистике, а также закономерности реализации языковых единиц в речевом процессе. В статье проводится сравнительный анализ природы языка как статической системы и речи как динамического явления. Также освещаются особенности вариативности фонем, морфем и лексем в речевой цепи, взаимосвязь языковой нормы и речевой вариантности. Ключевие слова: Язик, речь, лингвистика, реализация, языковая единица, речевая единица, парадигма, синтагма, вариант, инвариант, речевая деятельность, система языка Abstract. This article explores the interpretation of the language and speech dichotomy in modern linguistics, as well as the patterns of the realization of linguistic units in the speech process. The article provides a comparative analysis of the nature of language as a static system and speech as a dynamic phenomenon. It also highlights the features of variation of phonemes, morphemes, and lexemes in the speech chain, and the relationship between linguistic norms and speech variability. Key words: Language, speech, linguistics, realization, linguistic unit, speech unit, paradigma, syntagma, variant, invariant, speech activity, language system.
Background: Along with the development of sociolinguistic studies and language education, the orientation of research and learning practices is shifting from a monolingual approach to a more inclusive multilingual framework. In this context, translanguaging is seen as a communicative practice that allows individuals to use the entirety of their linguistic resources dynamically to build meaning, form identity, and establish social relationships. Purpose: This study aims to explore the practice of translanguaging within English Area communities that function as Community of Practice (CoP), focusing on the role of such practices in strengthening social cohesion as well as in the identity negotiation process between core members and outsiders of the community. Method: This research applies ethnographic case study approach. Data collection was conducted through participatory observation, semi-structured interviews, and review of community documents involving various actors, ranging from core administrators, active members, new members, former members, to external observers. Data analysis was conducted using Thematic Analysis to reveal patterns of language use, linguistic norms that develop, and the dynamics of social identity formation in the community. Results and Discussion: Research findings show that the English Area acts as a community of practice that supports the collaborative and sustainable English learning process. The practice of translanguaging not only serves as a pedagogical strategy to facilitate the understanding of the material, but also as an effective strategy that contributes to decreasing language anxiety and increasing member engagement. The use of language in the community is flexible and situational, where English is applied in accordance with the goals of the activity and the level of readiness of the participants. Although the ability to speak English serves as a symbol of membership, the application of language flexibility actually strengthens the sense of community and reduces the potential for social exclusion. Conclusions and Implications: This study confirms that translanguaging plays an important role in language learning, identity formation, and the sustainability of communities of practice, and has implications for the development of more inclusive and contextual English learning practices.
KIParla is a large, modular corpus of spontaneous spoken Italian originally transcribed in ELAN using Jefferson-style conventions. While this representation preserves fine-grained interactional detail and time alignment, it limits interoperability, large-scale querying, and computational reuse. This paper presents the design and implementation of a pseudo-tokenized, verticalized pivot format developed to support validation, maintenance, and infrastructural integration without sacrificing descriptive richness. The proposed format makes explicit the analytical units implicit in Jefferson transcription—transcription units, spans, and tokens—and enforces well-formedness constraints at character, span, and unit levels. Overlap, the most complex relational phenomenon, is resolved through a graph-based algorithm that derives temporal overlap events from alignment data and deterministically matches them to textual spans. Each token is represented as a structured record enriched with lexical, prosodic, interactional, and alignment features, anchored through explicit character offsets. The vertical format functions as a maintained pivot representation from which alternative formats, including ELAN files and UD-compatible treebank representations, can be reproducibly derived. This architecture enables large-scale lemmatization, part-of-speech tagging, syntactic annotation, and cross-layer querying, while supporting version-controlled, DevOps-inspired workflows for sustainable corpus growth. The KIParla pivot format thus reconciles interaction-oriented transcription practices with computational standards and provides a model for reuse-oriented spoken-language data engineering.
Pronouns indicate significant importance in both pedagogical and communicative contexts, as they shape the way individuals are addressed and understood in social interactions and educational settings. Beyond the traditional pronouns “he” and “she,” the American Psychological Association endorses the scholarly use of the singular pronoun “they,” recognizing its relevance in promoting inclusive language practices. In addition, the popularity of neopronouns continues to rise, providing non-binary individuals with a broader range of linguistic options to express their identities. Despite this growing recognition, there remains a dearth of empirical research that systematically investigates the awareness, knowledge, and preferences regarding pronoun use among non-binary populations. Addressing this gap, the present quantitative inquiry examined the level of awareness, knowledge, and preference of pronouns among non-binary college students at a state university in the Philippines. The study involved 80 participants, including 20 lesbians, 20 gays, 20 bisexual males, and 20 bisexual females, selected through criterion sampling, who responded to a four-part researcher-developed survey questionnaire. The results indicate that, overall, non-binary college students are aware of the categories of pronouns (M=2.48, SD=0.39 for traditional pronouns; M=2.79, SD=0.25 for gender-neutral pronouns; and M=2.64, SD=0.32 for neopronouns) and knowledgeable about them (M=2.49, SD=0.31 for traditional pronouns; M=2.68, SD=0.23 for gender-neutral pronouns; and M=2.47, SD=0.32 for neopronouns). However, despite this awareness and knowledge, participants expressed a preference for using traditional pronouns (“he” and “she”) when being referred to. These findings underscore the persistence of traditional linguistic norms in educational settings and highlight the potential influence of formal language instruction on pronoun preference. Empirically, this study contributes to the limited body of research on non-binary pronoun use speficically in the Philippines, providing a foundational dataset that can inform inclusive language policies, pedagogical strategies, and future sociolinguistic investigations. Its significance lies not only in documenting patterns of pronoun awareness and preference but also in offering evidence-based insights for educators, policymakers, and advocates seeking to foster more inclusive and affirming learning environments.