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The term “charisma” is recognized as sociology's most successful export to common speech. While sociologists habitually dismiss popular uses of the word, we address its vernacularity head on as a worthy object of study and as a potential resource for conceptual development. Using machine learning, we locate “charisma” within the wider discursive field out of which it arises (and continues to arise) across four corpora; namely: Weber’s major writings; social scientific research (123,531 JSTOR articles); and social media (“X”) posts containing of “charisma” (n=77,161) and its 2023 variant, “rizz” (n=85,869). By capturing meaning structures that discursively suspend “charisma” across multiple dimensions, we discern three spectra that help to distinguish charisma’s sociological and non‐sociological uses. Spectrum one differentiates perspectives which see charisma as having either a structural or individual‐level range of efficacy. Spectrum two differentiates indifferent/analytical perspectives on charisma from perspectives which see it as desirable but also morally conservative. Spectrum three differentiates between relational and individualized ontologies for charisma. We find that, rather than hewing closely to the Weberian formulation, social scientific uses exist in an intermediate position vis‐à‐vis these three spectra. Thus, scholars participate in what they otherwise criticize as charisma’s vulgarization. The article concludes with recommendations for how to constructively interact with ‘popular charisma.’ [ABSTRACT FROM AUTHOR]

Byzantine Fault Tolerance (BFT) is crucial for ensuring the resilience of Distributed Machine Learning (DML) systems during training under adversarial conditions. Among the rising corpus of research on BFT in DML, there is no comprehensive classification of techniques or broad analysis of different approaches. This paper provides an in-depth survey of recent advancements in BFT for DML, with a focus on first-order optimisation methods, particularly, the popular one Stochastic Gradient Descent (SGD) during the training phase. We offer a novel classification of BFT approaches based on characteristics such as the communication process, optimisation method, and topology setting. This classification aims to enhance the understanding of various BFT methods and guide future research in addressing open challenges in the field. This work provides the foundations for developing robust BFT systems, using a variety of optimisation methods to strengthen resilience. [ABSTRACT FROM AUTHOR]

Using the Central Andean Chavín Phenomenon as a case study, this paper explores the middle ground between top-down (big data) and bottom-up (Bayesian modeling) approaches to archaeological radiocarbon data. Compiling radiocarbon dates associated with the Chavín Phenomenon addresses questions of chronology, demonstrating that the relevant phases at interacting sites are relatively brief and broadly contemporary. In addition, the definition of a discrete span of time associated with the Chavín Phenomenon makes it possible to explore the context for that period of heightened interaction. Juxtaposing that timespan with a compilation of Central Andean radiocarbon dates identifies contemporary non-participatory sites, enabling characterization of the sociopolitical milieu within which the Chavín Phenomenon emerged, flourished, and faded. The identification of that corpus of sites also highlights the importance of a shift in focus from identification of interaction to characterization of interaction. Bottom-up approaches to radiocarbon chronology will be a key element of that effort, while high-level summary of radiocarbon assemblages can identify where additional dating and Bayesian modeling can have the greatest interpretive impact. [ABSTRACT FROM AUTHOR]

A phrase-frame (p-frame) is a multi-word sequence with a one-word variable within the sequence (e.g., it is * to). P-frames are important components of language production and can demonstrate phraseological patterning. This study examined p-frames retrieved from one learner business emails corpus (1,413 texts based on the Education First-Cambridge Open Language Database) and one working professional email corpus (1,145 texts from the Enron email dataset). P-frames were investigated both quantitatively and qualitatively in terms of their structural characteristics, functional characteristics, and variability. Our results showed that the working professionals and the learners of business English used p-frames differently. The working professionals used p-frames in ways that aligned with written conventions, whereas the learners of business English used p-frames in ways that did not accord well with written conventions. This difference was detected by comparing tendencies in function-word frames and frames for referential function. In addition, p-frames used by the working professionals displayed a higher degree of variability than those by the learners of business English. This study facilitates an understanding of learners' p-frame use in English for business purposes and suggests that p-frames be incorporated into the teaching and learning of L2 business writing. [ABSTRACT FROM AUTHOR]

Analyzing the diachrony of Hebrew bein, originally a spatial preposition 'within/among', this article traces several grammaticization clines associated with bein's gradual evolution into a rich variety of functions within various constructions. While its early function is purely locative, bein later participates in an array of constructions and sub-constructions, where its syntactic status, its semantic meanings and functions, as well as its discourse role, have shifted considerably. Bein may thus be part of a conjunctive or a disjunctive construction, but it may also be part of an 'in any case' adverbial, and later an 'anyway' discourse marker. It conveys different locative construals ('within', 'among' and 'between'), but also various abstract symmetric relations, such as 'difference', 'dispute' and 'separation'. Some bein constructions partition a set, focusing on a subset of it, while in other cases bein serves as an 'all-purpose' preposition. Nevertheless, our goal is to show how each grammatical, semantic and discoursal phase is well motivated, given the previous phase. Based on written historical corpora, from Biblical to contemporary Hebrew, we provide a step-by-step diachronic development from earlier to later bein functions. [ABSTRACT FROM AUTHOR]

The aim of this article is to offer a systematic review of digital studies that provide new research perspectives on ancient classical theatre. The undeniable progress in the field of computational analysis in the service of traditional textual interpretation is helping to study in greater depth and to interpret in greater detail the classical linguistic corpora that have come down to us through the manuscript tradition. The new model of digital research is integrated not only in the field of information technologies, but also in the field of e-learning, where we can already observe the implementation of a new educational model. Based on the digital processing of data on Greco-Roman theatre, a systematic review is presented, following the methodological principles of the PRISMA statement [ Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2009 (2020)]. [ABSTRACT FROM AUTHOR]

This research focuses on classifying translated and non-translated Chinese texts by analyzing syntactic rule features, using an integrated approach of machine learning and entropy analysis. The methodology employs information entropy to gauge the complexity of syntactic rules in both text types. The methodology is based on the concept of information entropy, which serves as a quantitative measure for the complexity inherent in syntactic rules as manifested from tree-based annotations. The goal of the study is to explore whether translated Chinese texts demonstrate syntactic characteristics that are significantly different from those of non-translated texts, thereby permitting a reliable classification between the two. To do this, the research calculates information entropy values for syntactic rules in two comparable corpora, one of translated and the other of non-translated Chinese texts. Then, various machine learning models are applied to these entropy metrics to identify any significant differences between the two groups. The results show significant differences in the syntactic structures. Translated texts have a higher degree of entropy, indicating more complex syntactic constructs compared to non-translated texts. These findings contribute to our understanding of the effect of translation on language syntax, with implications for text classification and translation studies. [ABSTRACT FROM AUTHOR]

This article will analyze the use of the noun nafs ‘soul’ with the firstperson possessive pronominal suffix, through the corpus of Andalusi texts gathered in Nafḥ al-ṭīb by the North-African author Shihāb al-Dīn al-Maqqarī (d. 1632). The aim is threefold: one, to identify patterns of the use of nafsī in the Nafḥ, their semantic performance, and diachronic evolution; two, to compare the use of the term in this corpus with its use in lists of collocates in the macro corpora KSUCCA and arTenTen of Classical and Modern Standard Arabic; and three, to show that linguistically systematizing self-expression is adequate for the identification of highly subjective texts in a corpus. Analysis will show that the notions of the ‘divided self’, sacrificing oneself, and yearning change towards a closer relationship between the subject and the self over time. [ABSTRACT FROM AUTHOR]

Despite the critical role that datasets play in how systems make predictions and interpret the world, the dynamics of their construction are not well understood. Drawing on a corpus of interviews with dataset creators, we uncover the messy and contingent realities of dataset preparation. We identify four key challenges in constructing datasets, including balancing the benefits and costs of increasing dataset scale, limited access to resources, a reliance on shortcuts for compiling datasets and evaluating their quality, and ambivalence regarding accountability for a dataset. These themes illustrate the ways in which datasets are not objective or neutral but reflect the personal judgments and trade-offs of their creators within wider institutional dynamics, working within social, technical, and organizational constraints. We underscore the importance of examining the processes of dataset creation to strengthen an understanding of responsible practices for dataset development and care. [ABSTRACT FROM AUTHOR]

The phenomenon of the 'complaint tradition', expressing the belief that language standards are deteriorating in some way, has had a long and vibrant existence in discussions of English in Hong Kong. The contribution of a Cultural Linguistics perspective here highlights the nature and significance of the cultural conceptualisations of language, for example, those that are revealed by the use of metaphor. The article begins with an overview of the discourse in Hong Kong, based on a corpus of media articles. The discourse structure and content of the articles, including their metaphorical aspects, are then analysed in more detail. To help understand the persistence of the discourse I draw on the insight that metaphors constitute 'mini‐narratives' which construct identities and identity boundaries. The discussion considers how the prevailing conceptualisations of English—some general, and others more culturally specific—serve to reproduce dominant, standardising views and inhibit the acceptance of local variation. [ABSTRACT FROM AUTHOR]

Based on the analysis of a linguistic corpus, this study uses relevance theory (Sperber and Wilson, 1986/1995) to demonstrate that the Tunisian Arabic particle ha :, which has never received any research attention, acts as an attitudinal marker in addition to its vocative function. Namely, ha: is restricted to utterances in which the speaker is expressing negative emotion or a subtype of positive emotion that can only be directed at the addressee. The data analysis shows that, unlike its relatively unmarked and well-studied counterpart ya: , ha: is restricted in terms of its frequency of distribution and the types of speaker emotions and attitudes expressed in the utterance in which it occurs. This study argues that ha: encodes a procedure which instructs the hearer to recognize the speaker's emotion or attitude expressed toward them in the utterance. The particle ha: therefore, serves as an explicit additional guarantee of relevance that encourages the hearer to look for additional contextual assumptions in order to achieve the speaker's desired interpretation. • The choice between the two vocative particles ha: and ya: is not arbitrary. • The Tunisian Arabic particle ha: acts as an attitudinal marker. • ha: encodes a procedure guiding the hearer to recognize the speaker's emotions. • The particle ha: serves as an explicit additional guarantee of relevance. • The particle ha : is no always compatible with the speaker's preferences. [ABSTRACT FROM AUTHOR]

Speech enhancement performance has improved significantly with the introduction of deep learning models, especially methods based on the Long–Short-Term Memory architecture. However, these methods face challenges such as high computational complexity and redundancy of input features. To address these issues, we propose a U-Net-based approach that utilizes an encoder/decoder to extract more concise features, thereby enhancing single-channel speech performance and reducing computation complexity. The proposed method includes a Cross-Swin-Transformer block and a masked bottleneck module, which down-samples features while preserving the detailed representation through skip connections and carefully designed blocks. The bottleneck module extracts coarse representations of hidden features as masks. We evaluated our method against other U-Net-based approaches on VCTK and DNS corpora using CBAK, eSTOI, PESQ, STOI, and SI-SDR metrics. The results demonstrate that the proposed method achieves promising performance while significantly reducing computational complexity. [ABSTRACT FROM AUTHOR]

The learning quality of humans depends on the sense of contemplation. Textual documents are a huge part of the literature on contemplation which effortlessly creates perception. Automatic document class identification or organisation is a machine learning function to understand the psychological and emotional content of the text in a concise way. The problem of identification of documents falls in the field of library science, information science and artificial intelligence. The research progress of class identification of documents has been made in various most spoken languages. Numerous research works have been published in European and Asian languages. However, there is a gap in the literature when it comes to any less resource language, especially Bengali. Consequently, this work portrays an efficient topic modelling approach for Bengali document class identification. It proposes a Dirichlet-polynomial clustering model likelihood corpus distribution (LCD), which is based on a Bayesian numerical prototype. Experiments are done to prove the efficiency of LCD over various topic modelling algorithms, such as latent Dirichlet allocation (LDA), LDA with bag-of-words (LDA-BOW), latent semantic indexing (LSI), and hierarchical Dirichlet process (HDP). For performance evaluation, we considered five real-world datasets of Bengali corpora, such as science, sports, computer, season, and epic in this work. The coherence score of different modelling algorithms is compared to find the best model for each dataset separately. [ABSTRACT FROM AUTHOR]

The ability to assign meaning to perceptual stimuli forms the basis of human behavior and the ability to use language. The meanings of things have primarily been probed using behavioral production norms and corpus-derived statistical methods. However, it is not known to what extent the collection method and the language being probed influence the resulting semantic feature vectors. In this study, we compare behavioral with corpus-based norms, across Finnish and English, using an all-to-all approach. To complete the set of norms required for this study, we present a new set of Finnish behavioral production norms, containing both abstract and concrete concepts. We found that all the norms provide largely similar information about the relationships of concrete objects and allow item-level mapping across norms sets. This validates the use of the corpus-derived norms which are easier to obtain than behavioral norms, which are labor-intensive to collect, for studies that do not depend on subtle differences in meaning between close semantic neighbors. [ABSTRACT FROM AUTHOR]

Grounding language in vision is an active field of research seeking to construct cognitively plausible word and sentence representations by incorporating perceptual knowledge from vision into text-based representations. Despite many attempts at language grounding, achieving an optimal equilibrium between textual representations of the language and our embodied experiences remains an open field. Some common concerns are the following. Is visual grounding advantageous for abstract words, or is its effectiveness restricted to concrete words? What is the optimal way of bridging the gap between text and vision? To what extent is perceptual knowledge from images advantageous for acquiring high-quality embeddings? Leveraging the current advances in machine learning and natural language processing, the present study addresses these questions by proposing a simple yet very effective computational grounding model for pre-trained word embeddings. Our model effectively balances the interplay between language and vision by aligning textual embeddings with visual information while simultaneously preserving the distributional statistics that characterize word usage in text corpora. By applying a learned alignment, we are able to indirectly ground unseen words including abstract words. A series of evaluations on a range of behavioral datasets shows that visual grounding is beneficial not only for concrete words but also for abstract words, lending support to the indirect theory of abstract concepts. Moreover, our approach offers advantages for contextualized embeddings, such as those generated by BERT (Devlin et al, 2018), but only when trained on corpora of modest, cognitively plausible sizes. Code and grounded embeddings for English are available at (https://github.com/Hazel1994/Visually_Grounded_Word_Embeddings_2). [ABSTRACT FROM AUTHOR]

Objective: This study proposes a cephalometric method to determine an individual radius of the curve of Spee in cases of occlusal prosthetic rehabilitation. Methods: A retrospective study was conducted on 469 lateral cephalograms. Statistical analysis was performed. Correlations were computed using simple regression, Z tests, paired t-tests, and one-way repeated measures ANOVA. Results: Regression calculations supported a link between the radius of the curve of Spee and occlusal plane inclination, Balkwill's angle, mandibular parameters (MP), with MP = corpus – ramus + Bonwill height. Based on MP, data that are accessible even in the absence of teeth, a regression formula can be proposed to provide an individualized estimation of the radius of the Spee curve (RCS): RCS = 0.624 * MP + 26.583. Conclusion: This study proposes an individualized estimation of the RCS from only skeletal mandibular parameters: the length of the ramus, length of the corpus, and the Bonwill height. [ABSTRACT FROM AUTHOR]

The launch of the FrameNet project in 1997 was both a crystallisation point of decades worth of theoretical investigations into lexical meaning by Charles J. Fillmore and colleagues, as well as the seed of an ongoing line of corpus-based and computational research that seeks to implement Fillmore's theory of Frame Semantics in a way that both provides an interesting model relevant for further theorising and also is applicable practically for semantic analysis, lexicology, and lexicography. At the occasion of FrameNet's 25th birthday, we want to introduce the project to a new generation of researchers but also take stock of, and report on, what has been achieved. We revisit the origins of the FrameNet project, assess its development and various changes in the years since it was first reported on in a special issue in the pages of this journal twenty years ago. [ABSTRACT FROM AUTHOR]

The Persian verb "xâstan" exhibits a dual nature, functioning both as an auxiliary verb and a lexical verb. As a lexical verb, it conveys a range of meanings expressed through various syntactic structures. This research delved into the syntactic and semantic aspects of the mentioned verb in different constructions. The authors proposed that Role and Reference Grammar (RRG), with its focus on complex structures, could provide a comprehensive framework for analyzing the constructions under consideration. RRG conceptualizes complex structures based on "Interclausal Relations Hierarchy", which comprises two syntactic and semantic continua. The syntactic continuum examines juncture -nexus relations, while the semantic continuum explores the type of semantic relations based on the main predicate. This study endeavored to describe the various applications of the verb "xâstan" within the mentioned framework. Additionally, the research findings were employed to evaluate the tenets of RRG. The findings revealed that, semantically, the verb "xâstan" fell within the categories of psych -action, jussive, and propositional attitude predicates. Syntactically, it manifested in the forms of core cosubordination and core subordination. The data for this research were extracted from the corpus of Hamshahri 2. [ABSTRACT FROM AUTHOR]

Stylized neural machine translation (NMT) aims to translate sentences of one style into sentences of another style, it is essential for the application of machine translation in a real-world scenario. Most existing methods employ an encoder-decoder structure to understand, translate, and transform style simultaneously, which increases the learning difficulty of the model and leads to poor generalization ability. To address these issues, we propose a curriculum pre-training framework to improve stylized NMT. Specifically, we design four pre-training tasks of increasing difficulty to assist the model to extract more features essential for stylized translation. Then, we further propose a stylized-token aligned data augmentation method to expand the scale of pre-training corpus for alleviating the data-scarcity problem. Experiments show that our method achieves competitive results on MTFC and Modern-Classical translation dataset. [ABSTRACT FROM AUTHOR]

Few-shot relation classification (RC) is a crucial task that aims to identify the relationships between entity pairs with limited mentions. However, this task is challenging due to the insufficient amount of annotated data. Augmenting the quantity of annotated instances provides a reasonable solution, which is typically realized through distant supervision (DS). However, this approach may introduce substantial noise and negatively impact model performance. Conversely, prompt learning (PL) improves the quality of annotated instances by enabling the models to understand the input text thoroughly with templates. Unfortunately, these templates mainly neglect the semantics of labels. To address these issues, we propose coarse-to-fine filters with concept heuristic prompt (CoFF-CHP), which employs dual-stage filters to select and label reliable instances from unlabeled corpus. Specifically, we first employ the coarse-grained filters to preliminarily select the instances. Next, we design a fine-grained filter, concept heuristic prompt (CHP), which can integrate the semantics of the label concept to help the model understand the link between the input text and labels. Finally, to reduce the tilt toward positive instances, we incorporate the screen-out data and false-positive instances to form the negative set to correct the classifier. The experimental results on the public Fewrel dataset indicate that CoFF-CHP achieves state-of-the-art performance in low-resource scenarios, especially when the best baseline is upgraded by 15.06% in terms of F1 in the setting of 10 seed instances. [ABSTRACT FROM AUTHOR]

This paper introduces readers to the TESOL Quarterly special topic issue: Assessing the effectiveness of corpus‐based approaches to English language teaching. The authors open by briefly defining and outlining data‐driven learning (DDL) research on second language (English) teaching. This is followed by an extended discussion of four themes, which pertain to recent developments and future directions in DDL. These themes include: (1) selecting corpora for corpus‐based language teaching; (2) pushing the boundaries of DDL; (3) preparing language educators for corpus‐based language teaching; and (4) reflecting on theory and methods. Throughout the piece, readers are also introduced to those contributions within the special issue, which include a diverse range of pieces that focus on aspects of theory, research, and pedagogy. [ABSTRACT FROM AUTHOR]

The use of academic corpora in second language (L2) writing pedagogy has gained popularity in recent decades, particularly in genre‐specific contexts for graduate‐level L2 students (Charles, 2007; Lee & Swales, 2006). However, its overall effectiveness is mainly observed within classroom contexts, influenced by various contextual and participant‐related factors (Vyatkina & Boulton, 2017). Moreover, these investigations have predominantly relied on retrospective data useful for understanding learners' perception of corpus‐analysis experiences, but not for how learners strategically integrate corpora into personal toolkits for self‐directed writing tasks. Addressing these gaps, this study tracks five Chinese EFL graduate students' corpus use through a 5‐week concept‐ and corpus‐based tutoring intervention and investigates how they navigated a discipline‐specific corpus alongside other digital resources during post‐intervention self‐directed revisions. By triangulating screen recordings with retrospective data (questionnaires, interviews, draft revisions, and stimulated recalls), the results showed that while participants were generally favorable toward the specialized corpus and its complementary role to personal toolkits, individual problem‐solving patterns in revision revealed less overall reliance on the corpus and its effectiveness primarily in addressing known linguistic problems. Implications for a relational understanding of digital tools support and the integration of other pedagogical activities in L2 writing instruction are discussed. [ABSTRACT FROM AUTHOR]

Data‐driven learning (DDL) is an increasingly popular area of research for language teaching and is gradually being incorporated into teacher education programs globally. However, assessing teacher trainees' (self‐reported) corpus literacy, and its impact on eventually (and successfully) incorporating corpora into language teaching, is an ongoing issue. This paper explores the experiences of in‐service English language teacher trainees in developing both corpus literacy and corpus‐based language pedagogy skills in Vietnam. The study finds a disconnect between participants' high self‐reported corpus literacy skills, high intention to conduct corpus‐based language teaching, and their ability to convert said intention and literacy into viable ideas for corpus‐based language teaching within their lesson planning. Potential reasons include difficulties conceptualizing DDL's integration into lesson objectives, selection of inappropriate corpora for the target audience, issues planning DDL activities for primary‐age learners, and Vietnamese‐specific issues mainly around access to technology. Accordingly, we present several recommendations for improving the assessment of DDL trainees' actual integration of DDL into their teaching practice. [ABSTRACT FROM AUTHOR]

Learner corpora have been used extensively in corpus research to identify gaps and errors within learner writing but have rarely been directly used in corpus‐informed instruction (CII). Importantly, scholars in CII have pointed out that "it is as important to see what learners can do as well as what they can't" when using learner corpora (Boulton & Thomas, 2012; p. 13). Learner corpora can also offer greater alignment with the genres students are writing (Seidlhofer, 2002). In our Brief Report, we take up Lu, Casal, and Liu's (2021) call for greater synergy of genre and corpus pedagogy by examining the impact of using a learner corpus to enhance students' language awareness and genre‐specific knowledge within an English as an Additional Language (EAL) first‐year writing classroom. We also move beyond error analysis to encourage an asset‐based model to learner CII (Staples, 2022). [ABSTRACT FROM AUTHOR]

This paper discusses the development and implementation of a locally‐sourced corpus to address the specific needs of an ESL writing program. The paper begins with a description of the motivation and development of the Corpus of Ohio Learner and Teacher English (COLTE), a large in‐house corpus consisting of assessed ESL student writing and teacher feedback from first‐year writing courses. The paper illustrates research conducted within the local context using the COLTE and discusses how the program's corpus‐based approach influenced curricular revisions and instructional practice. It addresses the evaluation of these efforts, challenges encountered, and considerations for building and using corpora at the program level. The paper concludes by arguing that stakeholders within programs can work collaboratively to build and use locally‐sourced corpora grounded in their specific setting to explore local practices and address the English language learning and teaching needs of their own particular context. [ABSTRACT FROM AUTHOR]

This paper analyses the methodologies in 148 empirical data‐driven learning studies for L2 English in prestige journals to examine best practice. Manual coding and corpus analysis of key words and n‐grams from the past 5 years (2018–2022) explore the field as a whole and how methodologies have evolved, suggesting improvements and future avenues for research. [ABSTRACT FROM AUTHOR]

The article discusses the integration of corpora into language teaching, emphasizing its benefits and the challenges in mainstream adoption. Topics include the underuse of corpora in teaching due to a lack of user-friendly resources, the potential for teachers to enhance their instructional decisions and materials through corpus-based insights, and the author's observations of students learning to use a corpus in an academic writing module.

The article introduces triangulation to converge evidence from corpus and experimental data, by means of two case studies in second language (L2) learners of Greek. The first case study investigates the acquisition of gender agreement, while the second probes the development of relative clauses. In both studies, findings from the corpus are tested against online experimentation using eye‐tracking and self‐paced reading tasks, a combination that is scarce in research implementing triangulation. The findings suggest that methodological convergence yields both congruous and incongruous evidence. However, both types of evidence contribute to a nuanced understanding of the linguistic phenomena under study, as well as the different perspectives from which they are approached. The article concludes that such an approach to triangulation can significantly contribute to enhancing the reliability and validity of the findings, provided that methodological convergence has been achieved at the design level of the study. [ABSTRACT FROM AUTHOR]

A perennial topic of research on giftedness has been individuals' perceptions of and attitudes towards giftedness, the gifted, and gifted education. Although giftedness is a culturally constructed concept, most examination of the term's meanings and implications has used reactive measures (i.e., surveys) to tap respondents' giftedness-related perceptions and attitudes within the context of formal education. To provide a better understanding of the cultural meanings associated with giftedness—the term's cultural framing—we investigated the depiction of giftedness within a professional cultural product removed from education, namely, a large corpus of US fictional texts. We examined patterns of word usage in the vicinity of the term gift*, when used in the dictionary senses related to giftedness, in a large corpus of US fictional texts of recent decades, consisting of 485,179 text samples and 1,002,889,754 word tokens. Via inductive methods of quantitative text analysis, we explored themes occurring in the vicinity of gift*; and with an existing lookup dictionary, we assessed deductively the overall emotional valance of the writing near gift*. Our investigation revealed ways in which the literary exploration of giftedness coheres with and distinguishes itself from the outlooks on giftedness noted for survey-based research in education settings. In fictional texts, giftedness evinces special associations with humanities domains and beauty and, on balance, correlates positively with emotionally positive words. [ABSTRACT FROM AUTHOR]

Summary This paper first describes the difficulties in providing the required sample sizes for clinical trials that guarantee type 1 and type 2 error control. The required sample sizes obviously depend on the test employed, and in this study we use the so‐called E‐test, which is known to have extremely favourable size properties and higher power than alternatives. To compute exact powers for this test in real time is not currently feasible, so a corpus of pre‐computed exact powers (and sizes) was created, covering sample sizes up to 500. When there are no solutions within the corpus, a novel extrapolation technique is used. Exact size can be computed after the sample sizes have been extracted; however, for the E‐test the exact size is virtually always very close to the nominal target. All the code has been converted into an R‐package, which is available on CRAN and illustrated. [ABSTRACT FROM AUTHOR]

The following article is committed to diachronic text linguistics. It aims to discuss the transformation processes of (media) text genres using the example of the weather forecast. The focus is on the development of a specific programme over the last 40 years on the German television channel ARD. The study examines the changes of the TV weather forecast over the course of the period under investigation and as a consequence how widely its programme has varied and to what extent it has been standardized. Based on the standard features of the weather forecast, I attempt to clarify the differences in its text-genre-specific and stylistic design using the selected corpus. The processes of change are thus described from a text-linguistic point of view, whereby the changes at the level of the communication situation, text function, text structure, topic or sub-topics, as well as the multimodal constitution of the text are analysed. The aim of the study is to determine which features can be observed over the years in the established text genre of the selected television weather forecast, and how they can be explained. In this way, understanding of the processes of change in media texts will hopefully be furthered. [ABSTRACT FROM AUTHOR]

We report the discovery of a vast corpus of indigenous legal contracts (‘arraten’) in the Morocco Atlas Mountains. The documents comprise about 400 years of written records. A collection of this magnitude has never before been reported, and such documents have not as of yet been systematically amassed for examination, preservation and study. The amount of documents discovered by us, and remaining in situ, is likely to exceed 5000 items. This is in addition to our own private collection which is in excess of 4000 pieces. We estimate that the entire body of documents written on wood in the Anti-Atlas Mountains is likely to be no less than 100,000 pieces and may very well exceed 500,000. In addition to this, between 40,000 and 150,000 paper documents likely exist. Here we report our preliminary studies of those manuscripts. Our collection is available to anyone and donation to suitable institutions will be considered. [ABSTRACT FROM AUTHOR]

Boris Pahor was born in 1913 in Trieste, where he died at the age of 108. In all his works, he tries to reconstruct the conditions of exclusion experienced by himself, his family, his people, and finally all those who resisted the ideological pressures at the height of the Nazi terror, as described in the novel Necropolis (1967). The extreme violence with which assimilation was imposed on the Slovenian minority did not allow him to preserve his original identity. Pahor’s Trieste confirms that spaces exposed to a constant pressure of assimilation are spaces of undeniable vitality. This perspective should allow us to create a corpus of knowledge that reflects the resilience of cultures exposed to domination. Instead of seeing the margins as a place of exclusion and endemic difficulties, we need to change the narrative that defines them. Margins are the spaces where translation constantly materializes, the spaces of exchanges and transfers, thus the periphery has the capacity for mediation between complex cultural systems. [ABSTRACT FROM AUTHOR]

This study employs a corpus-based approach to examine and compare the use of two discourse markers (DMs), "you know" and "I mean", within the context of two mediatised English political interviews. The analysis encompasses frequencies, functions, co-occurrences, and positional distributions of these DMs. The study utilizes specialized corpora from two political interview programs: CGTN's The Point with Liu Xin and BBC's HARDtalk. The frequency analysis reveals that "you know" is statistically more prevalent than "I mean" in both programs, reflecting the spontaneity, interactivity, and need for clarification characteristic of political interviews. Notably, the Chinese interviewer (IR) uses "you know" more extensively, possibly due to a cultural preference for ensuring mutual understanding and engaging the audience, while the British IR employs "I mean" slightly more frequently, likely reflecting a tendency to clarify or reframe statements for precision. Functionally, these DMs serve diverse purposes such as hedging, agreeing, and monitoring across various domains including interpersonal, sequential, and rhetorical. Positional analysis shows "you know" typically appearing medially and "I mean" often in initial positions. These results underscore the distinctive interviewing styles of the two IRs and the pivotal role of these DMs in fulfilling a spectrum of communicative functions. This research offers valuable insights into the interviewer's perspective in political interviews. [ABSTRACT FROM AUTHOR]

Based on a new Turkish social media influencer corpus consisting of 30 YouTube vlogs, this study explores young adults' translanguaging practices, prevalent linguistic events, and spatial repertoires in communication. The analysis focuses on vlogs, where linguistic resources become available in relation to the activities, audience, and organization of places or objects and young adults' translanguaging practices and their situated functions. The findings demonstrate how to use translanguaging as a comprehensive methodology to analyze communication unfolding with multimodal, multilingual, and digital semiotic repertoires at speakers' disposal and for the imagined audience integral to the communication in vlogs. Taking a corpus-linguistics perspective to translanguaging, we propose a usage-based focus and undertake a broader understanding of translanguaging as a linguistic and multimodal phenomenon. 30 YouTube vlogundan oluşan yeni bir Türk sosyal medya etkileyicileri derlemine dayanan bu çalışma, genç yetişkinlerin diller ötesi pratiklerini, vloglarda hakim olan dilsel olayları ve iletişimdeki mekansal repertuarlarını incelemektedir. Analizin odağında genç yetişkinlerin dilsel kaynaklarının, etkinlikler, izleyici ve mekanların veya nesnelerin düzenlenmesi, diller ötesi pratikler ve bu pratiklerin yerleşik işlevleri ile ilişkili olarak kullanılabilir hale geldiği vloglar bulunmaktadır. Bulgular, vloglardaki iletişimin ayrılmaz bir parçası olan hayali izleyici için üretilen iletişimin konuşmacıların tasarrufunda olan çoklu modlu, çokdilli ve dijital göstergesel repertuarlar ile bir bütün olduğunu ve bu iletişimi çözümlemek için kapsamlı bir metodoloji olan diller ötesilik kuramının kullanılabileceğini göstermektedir. Bu çalışma, diller ötesiliği derlembilim destekli bir yaklaşımla ele alarak, kullanıma dayalı bir odak önermekte ve diller ötesiliği dilbilimsel ve çok modlu bir olgu olarak daha kapsamlı bir anlayışla ele almaktadır. In our research, we look at how people use language in their everyday online videos (vlogs). Central to our study is the concept of translanguaging. It is a practical theory of language that helps us understand how people use different languages together, get creative with language, and create new ways of communicating online. This perspective goes beyond the traditional view, which treats multilingualism as simply switching between distinct linguistic systems. This is especially important on social media where global and local influences interact, and users access new activity spaces. We built a specialized corpus that contains 30 vlogs of six Turkish social media influencers on YouTube and used software called ELAN. This helped us analyze how they use both languages and visuals to communicate. What we found is that these influencers translanguage, use unique expressions, and include visual elements to connect with their audience online. Our study also emphasizes how interpreting and self--interpreting in translanguaging helps convey meaning for an imagined audience. By studying these practices, we learn more about how language works in today's social media spaces and how it challenges our traditional conceptions of language. [ABSTRACT FROM AUTHOR]

Motivation Biomedical entity linking (BEL) is the task of grounding entity mentions to a given knowledge base (KB). Recently, neural name-based methods, system identifying the most appropriate name in the KB for a given mention using neural network (either via dense retrieval or autoregressive modeling), achieved remarkable results for the task, without requiring manual tuning or definition of domain/entity-specific rules. However, as name-based methods directly return KB names, they cannot cope with homonyms, i.e. different KB entities sharing the exact same name. This significantly affects their performance for KBs where homonyms account for a large amount of entity mentions (e.g. UMLS and NCBI Gene). Results We present BELHD (Biomedical Entity Linking with Homonym Disambiguation), a new name-based method that copes with this challenge. BELHD builds upon the BioSyn model with two crucial extensions. First, it performs pre-processing of the KB, during which it expands homonyms with a specifically constructed disambiguating string, thus enforcing unique linking decisions. Second, it introduces candidate sharing, a novel strategy that strengthens the overall training signal by including similar mentions from the same document as positive or negative examples, according to their corresponding KB identifier. Experiments with 10 corpora and 5 entity types show that BELHD improves upon current neural state-of-the-art approaches, achieving the best results in 6 out of 10 corpora with an average improvement of 4.55pp recall@1. Furthermore, the KB preprocessing is orthogonal to the prediction model and thus can also improve other neural methods, which we exemplify for GenBioEL, a generative name-based BEL approach. Availability and implementation The code to reproduce our experiments can be found at: https://github.com/sg-wbi/belhd. [ABSTRACT FROM AUTHOR]

While slope is a topic in the algebra curriculum, having a robust understanding of slope is needed for students to truly understand several single and multivariable calculus topics with any depth. We begin with a review of the topic of slope and present what is known from its existing corpus of literature. We then outline the tenets of APOS theory. Building from there, we suggest what a robust, flexible understanding of slope involves, as well as how slope is used, with the APOS-slope framework acting as a theoretical lens. This is followed by the cases of two hypothetical students built from amalgamations of research and experience to emphasize why moving easily between different ways of thinking about and the various uses of slope is vital to successfully transition into calculus. We offer suggestions as to how university instructors might consider slope understanding when teaching calculus, then conclude with suggestions for future research on slope. [ABSTRACT FROM AUTHOR]

This article examines the depiction of the Belt and Road Initiative (BRI) in elite English media across Europe to discern sentiments and ideological disparities between China and the Western world. Using the PRISMA method, 1826 relevant research articles on the BRI were identified, and 42 were selected for detailed analysis. Additionally, 1357 news articles from the Financial Times, The Guardian and BBC from 2015 to 2023 underwent linguistic corpus analysis. Employing a three-dimensional critical discourse analysis (3d-CDA), the study scrutinized sample news articles, revealing ideological underpinnings across various dimensions and frames. The analysis indicates a growing negativity towards the BRI in European English media, with sentiments averaging 38% from 2015 to 2023 and peaking at 56% and 54% in 2022 and 2023, respectively. Ideological differences often discussed in academic circles include a contrast between the emphasis on individualism in the West and the values of collectivism prominent in Chinese culture. However, it is important to recognize the diversity within these broad categories. This research offers insights for BRI stakeholders and enriches academic discourse with updated data. Its novelty lies in its dual-tiered approach to news relevance for content analysis and the application of three-dimensional CDA to BRI news discourse, revealing ideological disparities not previously explored. [ABSTRACT FROM AUTHOR]

Analysis of online user-generated reviews has attracted extensive attention with broad applications in recent years. However, the high-volume and low-value density of online reviews bring challenges to a timely and effective data utilization. To address that challenge, this work proposes an unsupervised review filtering method based on the inherent tree-structured hierarchies among review data that reflect the general-to-specific characteristics of various quality aspects discussed in reviews. In particular, the reviews with aspects distributed near the leaf nodes of the tree are capable of providing more specific and detailed information about the examined product, which is more likely to be reserved after the tree-based filtering. To enable an effective extraction of aspect hierarchies from a broad variety of review corpora, a Bayesian nonparametric hierarchical topic model has been constructed and incorporated with an enhanced Pólya urn scheme. The approximate inference of model parameters is obtained by an efficient collapsed Gibbs sampling procedure. The proposed method can enhance the layered effect of individual reviews according to their general-to-specific characteristics and reserve an information-rich subset filtered from the raw review corpus. The merits of the proposed method have been elaborated by case studies on two real-world data sets and an extensive simulation study. [ABSTRACT FROM AUTHOR]

As a corpus-assisted method for language pedagogy, DDL (data-driven learning) may have the potential to enhance language exposure and promote active learner engagement. Concordancing, or KWIC (Key Words in Context), has been the traditional method used in DDL to retrieve numerous language examples, while the method has limitations with overreliance on individual words to search. This paper aims to propose and promote concordancing alternatively based on grammar patterns, a multi-word concept in corpus linguistics. The conceptualised method is named as PIC (Patterns in Context), an extended form of KWIC. An empirical study was conducted to investigate whether the PIC method has any advantages over the traditional KWIC method, using two custom-built Android apps. The research involved 18 pre-university intermediate learners (and six pilot study participants), who used the apps in a self-directed way for two weeks. Then the assessment of the two apps and methods was conducted based on data from automatic logs and responses from questionnaires and interviews. The results suggest that, compared to KWIC, PIC could be slightly advantageous in efficiently helping learners find the target language use, while this approach seems not strong in user engagement and perceived effectiveness. The implications for DDL are discussed, and further investigation is also planned. [ABSTRACT FROM AUTHOR]

Objective: This study was undertaken to delineate 21‐year sex‐specific trends in recurrence and postrecurrence mortality. Methods: Between 2000 and 2020, first‐ever ischemic stroke (IS) patients, ascertained from the population‐based BASIC (Brain Attack Surveillance in Corpus Christi) project in South Texas, were followed for recurrent stroke and all‐cause mortality until December 31, 2020. Multivariable regression models with an interaction between calendar year and sex were used to estimate sex‐specific trends and sex differences in recurrence and postrecurrence mortality. Results: Of the 6,057 IS patients (median age = 69 years, 49.8% women), 654 (10.8%) had a recurrence and 399 (47.7%) had postrecurrence mortality during 5 years of follow‐up. In 2000, women had 2.5% higher albeit non‐statistically significant 5‐year risk of recurrence than men in absolute scale. With the trend declining in women by 7.6% (95% confidence interval [CI] = −10.8 to −4.5%) and in men by 3.6% (95% CI = −6.5% to −0.7%), the risk at the end of the study period was 1.5% (95% CI = −0.3% to 3.6%) lower among women than men. For postrecurrence mortality, the risk was 10.2% lower among women in 2000, but the sex difference was 3.3% by the end of the period, which was due to a larger overall increase in the risk among women than men over the entire time period. Interpretation: The declines in recurrent stroke suggest successful secondary stroke prevention, especially in women. However, the continued high postrecurrence mortality among both sexes at the end of study period emphasizes the need for ongoing interventions to improve prognosis in those who have had recurrent cerebrovascular events. ANN NEUROL 2024;96:332–342 [ABSTRACT FROM AUTHOR]

Idiomatic expressions are not just neutral equivalents of their literal counterparts, but exert some sort of evaluative force. This study employed the appraisal system (AS) to explore the functions of idiomatic expressions and their variations in English as a lingua franca context, and to compare different academic domains in terms of use of evaluative language in the form of idiomatic expressions. To this end, the corpus of English as a lingua franca in academic settings and the Vienna–Oxford International Corpus of English were searched for idiom tokens through whole‐phrase and keyword search. The idioms and their variations were classified based on the AS. The findings indicated that social and behavioral scientific texts included higher proportions of evaluative idiomatic expressions whereas medical and natural scientific texts generated lower percentages of appraisal idioms. There was a stronger tendency in both corpora toward using idioms as appreciation as compared to judgment and affect. Given the employed methodology, the AS could not be applied to some idioms for their compositionality nature. [ABSTRACT FROM AUTHOR]

Copyright of Jahrbuch für Germanistische Sprachgeschicht is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Jahrbuch für Germanistische Sprachgeschicht is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An English-Bengali machine translation (MT) application can convert an English text into a corresponding Bengali translation. To build a better model for this task, we can optimize English-Bengali MT. MT for languages with rich resources, like English-German, started decades ago. However, MT for languages lacking many parallel corpora remains challenging. In our study, we employed back-translation to improve the translation accuracy. With back-translation, we can have a pseudo-parallel corpus, and the generated (pseudo) corpus can be added to the original dataset to obtain an augmented dataset. However, the new data can be regarded as noisy data because they are generated by models that may not be trained very well or not evaluated well, like human translators. Since the original output of a translation model is a probability distribution of candidate words, to make the model more robust, different decoding methods are used, such as beam search, top-k random sampling and random sampling with temperature T, and others. Notably, top-k random sampling and random sampling with temperature T are more commonly used and more optimal decoding methods than the beam search. To this end, our study compares LSTM (Long-Short Term Memory, as a baseline) and Transformer. Our results show that Transformer (BLEU: 27.80 in validation, 1.33 in test) outperforms LSTM ( 3.62 in validation, 0.00 in test) by a large margin in the English-Bengali translation task. (Evaluating LSTM and Transformer without any augmented data is our baseline study.) We also incorporate two decoding methods, top-k random sampling and random sampling with temperature T, for back-translation that help improve the translation accuracy of the model. The results show that data generated by back-translation without top-k or temperature sampling ("no strategy") help improve the accuracy (BLEU 38.22 , + 10.42 on validation, 2.07 , + 0.74 on test). Specifically, back-translation with top-k sampling is less effective ( k = 10 , BLEU 29.43 , + 1.83 on validation, 1.36 , + 0.03 on test), while sampling with a proper value of T, T = 0.5 makes the model achieve a higher score ( T = 0.5 , BLEU 35.02 , + 7.22 on validation, 2.35 , + 1.02 on test). This implies that in English-Bengali MT, we can augment the training set through back-translation using random sampling with a proper temperature T. [ABSTRACT FROM AUTHOR]

This study aims to examine Jordanian males’ comments on females’ physical appearance on Facebook to identify the impoliteness strategies that Jordanian males utilize in online communication. The socio-cultural factors affecting the selection of impoliteness behavior in males’ comments are also investigated. As for the corpus of the study, a total of 470 comments and replies were chosen from 32 females’ picture posts posted on two different Jordanian groups on Facebook. This study draws on Culpeper’s (1996) impoliteness framework. All Culpeper’s (1996) impoliteness strategies except withholding impoliteness (i.e., bald-on-record, sarcasm/mock, negative, positive) were employed. It was also found that making a clear boundary between different impoliteness strategies is not easy; more than one impoliteness strategy can be realized by the same expression. Furthermore, males were found to use other additional impoliteness strategies not mentioned in Culpeper’s (1996) impoliteness framework, namely, third-party implicit impoliteness, supplications, and negative interjections. The data analysis also revealed that some comments were subsumed under new categories not mentioned in previous (im)politeness frameworks: ambiguous (im)politeness and adversative (im)politeness. The use of such various strategies can be ascribed to the effect of socio-cultural and religious background on males’ behavior. [ABSTRACT FROM AUTHOR]

There is broad consensus that audio description (AD) is a modality of intersemiotic translation, but there are different views in relation to how AD can be more precisely conceptualised. While Benecke (Audiodeskription als partielle Translation. Modell und Methode, LIT, Berlin, 2014) characterises AD as 'partial translation', Braun (T 28: 302–313, 2016) hypothesises that what audio describers appear to 'omit' from their descriptions can normally be inferred by the audience, drawing on narrative cues from dialogue, mise-en-scène, kinesis, music or sound effects. The study reported in this paper tested this hypothesis using a corpus of material created during the H2020 MeMAD project. The MeMAD project aimed to improve access to audiovisual (AV) content through a combination of human and computer-based methods of description. One of the MeMAD workstreams addressed human approaches to describing visually salient cues. This included an analysis of the potential impact of omissions in AD, which is the focus of this paper. Using a corpus of approximately 500 audio described film extracts we identified the visual elements that can be considered essential for the construction of the filmic narrative and then performed a qualitative analysis of the corresponding audio descriptions to determine how these elements are verbally represented and whether any omitted elements could be inferred from other cues that are accessible to visually impaired audiences. We then identified the most likely source of these inferences and the conditions upon which retrieval could be predicated, preparing the ground for future reception studies to test our hypotheses with target audiences. In this paper, we discuss the methodology used to determine where omissions occur in the analysed audio descriptions, consider worked examples from the MeMAD500 film corpus, and outline the findings of our study namely that various strategies are relevant to inferring omitted information, including the use of proximal and distal contextual cues, and reliance on the application of common knowledge and iconic scenarios. To conclude, consideration is given to overcoming significant omissions in human-generated AD, such as using extended AD formats, and mitigating similar gaps in machine-generated descriptions, where incorporating dialogue analysis and other supplementary data into the computer model could resolve many omissions. [ABSTRACT FROM AUTHOR]

In complex stimuli, there are many different possible ways to refer to a specified target. Previous studies have shown that when people are faced with such a task, the content of their referring expression reflects visual properties such as size, salience, and clutter. Here, we extend these findings and present evidence that (i) the influence of visual perception on sentence construction goes beyond content selection and in part determines the order in which different objects are mentioned and (ii) order of mention influences comprehension. Study 1 (a corpus study of reference productions) shows that when a speaker uses a relational description to mention a salient object, that object is treated as being in the common ground and is more likely to be mentioned first. Study 2 (a visual search study) asks participants to listen to referring expressions and find the specified target; in keeping with the above result, we find that search for easy-to-find targets is faster when the target is mentioned first, while search for harder-to-find targets is facilitated by mentioning the target later, after a landmark in a relational description. Our findings show that seemingly low-level and disparate mental "modules" like perception and sentence planning interact at a high level and in task-dependent ways. [ABSTRACT FROM AUTHOR]

Previous academic research has argued that videogames are represented as violent in the media, and that these representations provide a justification to study videogames as a social object. However, little systematic research has been done to confirm whether such representations occur frequently, or whether this is a non-representative assumption based on a small number of news stories. Through using methods associated with Modern-Diachronic Corpus-Assisted Discourse Studies (md-cads), we explore two corpora of newspaper articles from the British press containing references to videogames: one contains data from 2000 and the other from 2020. We find that whilst newspapers do represent videogames as promoting violence, these representations occur much more frequently in 2000 than in 2020, and that in 2020 this idea is more regularly challenged. Furthermore, in 2020 there is a greater focus on the benefit of videogames for the economy compared to 2000. The research highlights the need to critically revaluate assumptions about how the media represents not only videogames, but also comparable topics. [ABSTRACT FROM AUTHOR]