ABSTRACT This study provides an in‐depth analysis of Chinaʼs film trade policies following its accession to the World Trade Organisation in 2001. It examines the factors behind the limited international success of Chinese films. Through a corpus‐based critical discourse analysis of nine national policy documents (2001–2020), the research investigates how the Chinese government has aimed to develop its domestic film industry while maintaining strict control over cultural trade. It finds a strategic shift toward a state‐regulated socialist cultural market, employing mechanisms such as censorship, licensing, import quotas, and state monopolisation to mitigate the influence of global trade liberalisation. The study also highlights the governmentʼs use of film festivals and exhibitions as tools for political propaganda, aligning them with foreign policy objectives and promoting official ideology. These practices underscore the tension between Chinaʼs aspirations for cultural soft power and its reliance on state control, which may hinder the global appeal of Chinese films.
In this paper, we study how different Reddit communities discuss generative AI in high school education, focusing on learning, academic integrity, AI detection, and emotional framing. Using 3,789 posts from five education-related subreddits, we compare student, teacher, and mixed communities using a pipeline that combines keyword retrieval, human-validated relevance filtering, LLM-assisted annotation, and statistical tests of group differences. We find that stakeholder position strongly shapes discourse: teachers are more likely to articulate explicit pedagogical trade-offs, simultaneously framing AI as both beneficial and harmful for learning, whereas students more often discuss AI tactically in relation to accusations, grades, and enforcement. Across all groups, detector-related discourse is associated with significantly higher negative emotion, with larger effects for students and mixed communities than for teachers. These results suggest that AI detectors function not only as contested technical tools but also as governance mechanisms that impose asymmetric emotional burdens on those subject to institutional enforcement. Finally, we argue that detection-based enforcement should not serve as a primary academic-integrity strategy and that process-based assessment offers a fairer alternative for verifying authorship in AI-mediated classrooms.
Objective Social media influencers—individuals with substantial, loyal followings—are influential in shaping public discourse, particularly among youth, on topics like health and well-being. However, their role in facilitating mental health discussions online remains underexplored. This study examines the perspectives of New Zealand (NZ) based influencers as part of a broader investigation into their engagement with mental health content. Methods This exploratory study employed remote, semi-structured interviews and reflexive thematic analysis. NZ-based influencers aged 16 and older, with over 10,000 followers and active on Instagram, TikTok, or YouTube, were recruited. Eight influencers (five females, three males, aged 26–45 years) participated, with a mean follower count of 53,000, predominantly on Instagram. Results Three key themes emerged, highlighting tensions within influencers’ roles. The first theme, “Defining Influence: Regular Person or Role Model,” explored their perspectives on their general power and identity as influencers. The second, “Discussing Mental Health: Amateur or Expert,” examined their self-perceived qualifications and challenges in creating public mental health content. The third, “Providing Crisis Support: Helpless Bystander or Well-Intentioned Samaritan,” detailed their approaches to responding to followers’ private mental health disclosures. Conclusions This study underscores the complex roles influencers play in youth mental health conversations, emphasizing their potential for positive impact alongside ethical and practical challenges. Clearer guidelines, targeted training, and resources are essential to equip influencers to engage safely, ethically, and effectively in these discussions. Influencers and mental health professionals could collaborate by establishing referral pathways and codeveloping psychoeducational or promotional content, while researchers, platforms, and policymakers may contribute by creating guidelines for responsible content distribution.
Computer applications to medicine. Medical informatics
The Environmental Impact Assessment (EIA) provisions form a crucial part of the Agreement under the United Nations Convention on the Law of the Sea on the Conservation and Sustainable Use of Marine Biological Diversity of Areas Beyond National Jurisdiction (the BBNJ Agreement) and are expected to have significant implications for States Parties. From a Chinese perspective, this study applies the SWOT-PEST analytical framework to examine the potential impacts of the BBNJ EIA rules on China.The findings reveal both opportunities and challenges across four dimensions: political, economic, social, and technological. Politically, China possesses certain policy and legal foundations, yet these are not fully developed, and while its international discourse power may expand, new regulatory barriers may arise. Economically, the healthy development of the marine economy supports the implementation of the new rules, however, in the short term, enterprises face multiple pressures such as rising costs and delayed returns, intensifying resource competition, while in the long run, this may facilitate their transformation and upgrading. Socially, despite existing gaps relative to international benchmarks, the engagement of diverse stakeholders provides a foundational basis for rule implementation, and although rising social pressures and adaptation costs present challenges, this also creates opportunities for multi-stakeholder development. Technologically, advancements in deep-sea technologies provide critical support for rule implementation while core technologies remain bottlenecked, facing threats from external technological barriers and simultaneously offering opportunities for cultivating marine technology expertise. Based on this analysis, the paper proposes potential strategies, including active participation in global ocean governance, advancement of deep-sea technologies, promotion of corporate transformation, and improvement of domestic legal frameworks
Science, General. Including nature conservation, geographical distribution
Arthur Buzelin, Pedro Robles Dutenhefner, Marcelo Sartori Locatelli
et al.
Social media networks have amplified the reach of social and political movements, but most research focuses on mainstream platforms such as X, Reddit, and Facebook, overlooking Discord. As a rapidly growing, community-driven platform with optional decentralized moderation, Discord offers unique opportunities to study political discourse. This study analyzes over 30 million messages from political servers on Discord discussing the 2024 U.S. elections. Servers were classified as Republican-aligned, Democratic-aligned, or unaligned based on their descriptions. We tracked changes in political conversation during key campaign events and identified distinct political valence and implicit biases in semantic association through embedding analysis. We observed that Republican servers emphasized economic policies, while Democratic servers focused on equality-related and progressive causes. Furthermore, we detected an increase in toxic language, such as sexism, in Republican-aligned servers after Kamala Harris's nomination. These findings provide a first look at political behavior on Discord, highlighting its growing role in shaping and understanding online political engagement.
We consider the numerical solution of high-frequency scattering problems modeled by the Helmholtz equation with a bounded obstacle. Although the analysis of this problem dates back at least 50 years, over the past decade or so, tools and techniques from $\textit{semiclassical analysis}$ have provided a new perspective and been used to settle several long-standing open problems in this area. Semiclassical analysis works in phase space (i.e., position and frequency) and describes rigorously the extent to which solutions of high-frequency PDEs are dictated by the properties of the corresponding geometric-optic rays. The goals of the article are to (i) give a introduction to semiclassical analysis aimed at non-experts and (ii) showcase some of the numerical-analysis results about finite-element methods, boundary-element methods, and domain-decomposition methods obtained using semiclassical techniques.
This article has four aims. First, it will consider explicitly, and polemically, the hierarchical relationship between conversation analysis (CA) and membership categorization analysis (MCA). Whilst the CA ‘juggernaut’ flourishes, the MCA ‘milk float’ is in danger of being run off the road. For MCA to survive either as a separate discipline, or within CA as a focus equivalent to other ‘generic orders of conversation’, I suggest it must generate new types of systematic studies and reveal fundamental categorial practices. With such a goal in mind, the second aim of the article is to provide a set of clear analytic steps and procedures for conducting MCA, which are grounded in basic categorial and sequential concerns. Third, the article aims to demonstrate how order can be found in the intuitively ‘messy’ discourse phenomenon of membership categories, and how to approach their analysis systematically as a robust feature of particular action-oriented environments. Through the exemplar analyses, the final aim of the article is to promote MCA as a method for interrogating culture, reality and society, without recourse to its reputed ‘wild and promiscuous’ analytic approach.
Issues around stigma and deservingness may be particularly salient for people who stop working due to health-related reasons. Although historically those experiencing disability have been viewed as “deserving” of assistance, disability has also been stigmatized. Using the American Voices Project data and narrative and discourse analysis methods, we ask how those with a health-related labor-market exit make sense of their exit. We find that respondents use various words to describe themselves with respect to their exit and that they use legitimization strategies when discussing why they do not work.
Interaktive Medien gehören in Zeiten zunehmender Digitalisierung längst zu den literarischen Erfahrungsräumen von Kindern und Jugendlichen. Ein Blick in den aktuellen literaturdidaktischen Forschungsdiskurs und den seiner Nachbardisziplinen zeigt jedoch: Die Potenziale des Interaktiven gelten als weitestgehend un- bzw. untererforscht. Im Rahmen des Beitrags werden daher Ergebnisse des empirischen Forschungsprojekts „Mehr als nur eine App“ vorgestellt, in dem in vier Einzelfallstudien erste Hinweise bezüglich der Nutzung interaktionsanregender Elemente in Bilderbuch- Apps für den Zugang zu literarischen Welten abgeleitet werden konnten (Mixed- Methods Design aus Eyetracking-Daten und Leitfadeninterviews, Auswertung qualitativ inhaltsanalytisch, App MirrorWorld, Schwerpunkt des Beitrags: Eyetracking-Auswertung). Hierzu werden aus dem aktuellen Forschungsdiskurs der Interaktionstheorie eine Arbeitsdefinition von interaktionsanregenden Strukturen in literarischen Rezeptionsprozessen abgeleitet und anschließend die empirischen Ergebnisse zur Nutzung von eben jenen Strukturen während zweier Explorationsrunden der Mirror-World-App vorgestellt (Schwerpunkt: Eyetracking-Daten, Heatmaps und Gaze-Analyse).
Abstract (english): „[…] you can simply discover more“ Interactivity as a (new) way of accessing literary worlds based on the example of the app mirrorworld
In times of increasing digitalization, interactive media have recently become part of the literary experience of children and young adults. However, a look at the current research discourse in literature didactics and its neighboring disciplines shows that the potentials of interactivity are largely unexplored or under-researched. This article therefore presents the results of the empirical research project „More than an App“, in which first indications regarding the use of interaction-stimulating elements in picture book apps for access to literary worlds could be derived in four individual case studies (mixed-methods design from eye-tracking data and guided interviews, qualitative content-analytical evaluation, app MirrorWorld, focus of the article: eye tracking analysis). For this purpose, a working definition of interaction-stimulating structures in literary reception processes is derived from the current research discourse of interaction theory, and subsequently the empirical results on the use of precisely those structures during two exploration rounds of the MirrorWorld app are presented (focus: eye tracking data, heat maps and gaze analysis).
Discourse Representation Structure (DRS) is an innovative semantic representation designed to capture the meaning of texts with arbitrary lengths across languages. The semantic representation parsing is essential for achieving natural language understanding through logical forms. Nevertheless, the performance of DRS parsing models remains constrained when trained exclusively on monolingual data. To tackle this issue, we introduce a cross-lingual training strategy. The proposed method is model-agnostic yet highly effective. It leverages cross-lingual training data and fully exploits the alignments between languages encoded in pre-trained language models. The experiments conducted on the standard benchmarks demonstrate that models trained using the cross-lingual training method exhibit significant improvements in DRS clause and graph parsing in English, German, Italian and Dutch. Comparing our final models to previous works, we achieve state-of-the-art results in the standard benchmarks. Furthermore, the detailed analysis provides deep insights into the performance of the parsers, offering inspiration for future research in DRS parsing. We keep updating new results on benchmarks to the appendix.
We constrain the parameters of the $k$-essence scalar field model with inverse square and exponential potentials using data sets including Pantheon+SHOES and the Dark Energy Survey (DES) of Type Ia supernovae, Baryon Acoustic Oscillation (BAO) data from SDSS and DESI surveys, and direct measurements of the Hubble parameter and redshift obtained from the differential age method (CC). We also provide a brief perspective on the dynamical evolution of both models and derive stability constraints on the model parameters, which are then used to set appropriate priors. We adopt a Bayesian inference procedure to estimate the model parameters that best fit the data. A comprehensive analysis in light of observational data shows that the $k$-essence model fits well across all data combinations. However, according to the BIC criterion, the $Λ$CDM model provides a slightly better fit compared to the $k$-essence model.
Annotation of political discourse is resource-intensive, but recent developments in NLP promise to automate complex annotation tasks. Fine-tuned transformer-based models outperform human annotators in some annotation tasks, but they require large manually annotated training datasets. In our contribution, we explore to which degree a manually annotated dataset can be automatically replicated with today's NLP methods, using unsupervised machine learning and zero- and few-shot learning.
We prove a universal projection theorem, giving conditions on a parametrized family of maps $Π_λ: X \to \mathbb{R}^d$ and a collection M of measures on X under which for almost every $λ$ equality $\dim_H Π_λμ= \min\{d, \dim_H μ\}$ holds for all measures $μ\in M$ simultaneously (i.e. on a full measure set of $λ$'s independent of $μ$). We require family $Π_λ$ to satisfy a transversality condition and collection M to satisfy a new condition called relative dimension separability. Under the same assumptions, we also prove that if the Assouad dimension of X is smaller than d, then for almost every $λ$, projection $Π_λ$ is nearly bi-Lipschitz (i.e. with pointwise $α$-Hölder inverse for every $α\in (0,1)$) at $μ$-a.e. x, for all $μ\in M$ simultaneously. Our setting encompasses families of orthogonal projections, natural projections corresponding to conformal iterated function systems, and non-autonomous or random IFS. As applications, we provide novel results on the multifractal analysis, giving formula for the Hausdorff dimension of a level set of the local dimension for a typical (w.r.t the translation parameter) self-similar measure on the line, valid for the full range spectrum (including the decreasing part of the spectrum; previous results were covering only the increasing part). Among another applications, we prove that given a parametrized contracting conformal IFS satisfying the transversality condition, for almost every parameter the dimension formula holds for all ergodic shift-invariant measures simultaneously. We also prove that the dimension part of the Marstrand's projection theorem holds simultaneously for the collection of all ergodic measures on a strongly separated self-conformal set and for the collection of all Gibbs measures on a self-conformal set (without any separation).
The research touches upon the innovations in the English word formation processes, i.e., the role
of analogy and intralingual borrowings as significant sources and ways of replenishing English vocabulary,
interfering entirely with all the languages in the world and greatly influencing their development.
Nominative units consisting of two or more words with a contraction of at least one of them at the place
of a junction, i.e., blends, are an integral feature of the English language in general and modern English
socio-political discourse in particular. Blending has been growing recently among the most productive
means of word formation. Blends are needed to denote new concepts and phenomena and are often
used to manifest the author’s word-formation skills; they become popular due to their expressiveness
and novelty of form and content. The goal of the article is to study the functional features of blends as a
means of strengthening the pragmatic component of the socio-political discourse, as well as the strategy
and techniques of their translation.
The general and special methods were used to achieve the goal and objectives of the study:
information retrieval method – to select research material and process basic theoretical knowledge;
generalization method – to highlight the most critical academic positions; deduction and induction – to
clarify the theoretical foundations, generalize data and formulate conclusions; discourse analysis – to
identify specific communicative and pragmatic features of socio-political communication; contextual and
functional methods – to actualize the linguopragmatic meaning of the lexical units under the study, i.e.,
blends; the vocabulary definitions analysis – to examine their linguopragmatic peculiarities; structuralsemantic and component analysis – to determine the ways of blend formation and their main structural
elements – all this is necessary for the implementation of translation analysis.
The use of pragmalinguistic elements (blends, in our case) involves investigating relationships
between language units and the conditions of the communicative-pragmatic space, tracing the relationship
between the addressee’s intentional component and the choice of language means when translating the
studied units within the socio-political discourse into another language.
Conclusions. Regarding the focus of socio-political discourse on speech influence, the conveying of
blend stylistics and the transfer of speech realia that form the basis of the blend implication and strengthen
the socio-pragmatics of the given text cause difficulties in comprehending the English original and
translation variants. The study of the translation aspect of blends within socio-political discourse revealed
a lot of challenges, such as the need for a unique means for conveying blend semantics in the translation
language, the complex nature of blend explication, and the problem of their interpretation.
Among the translation techniques that are most effective in overcoming the outlined translation
difficulties of socio-political blends, such ones should be mentioned first: transcription, transliteration,
tracing, and creating an analogical model. The descriptive translation method is considered inappropriate
when translating political blends (under research) because such a technique does not allow conveying
pragmatics of blends and implement them in the translation language as expressive lexical and stylistic
units that are components of speech influence on the addressee, and the society as a whole. The principles
of the techniques studied in the article can be used for further research as being universal for translating
English blends in inflectional languages (Ukrainian including), where such a phenomenon is non-typical. The
process of blending hypothetically proves the activation of the redistribution of components within the
different language structures and systems and their ability to self-reorganize.
María Victoria Martínez-Vérez, Pedro Javier Albar-Mansoa
Abstract The aim of the study is to analyze the evolution of gender roles and to generate, from a feminist and intergenerational perspective, a cognitive change in the participants, using film and discussion groups as mediating techniques, since they are considered appropriate to analyze the evolution of gender roles and to raise awareness, from a feminist and intergenerational perspective, about the importance of gender roles in people’s lives. To this end, an intergenerational project, called “ Women in the focus”, was created within the framework of the Master’s program at the Complutense University of Madrid, which allows 75 women, belonging to three different generations, to reflect on the concept of gender and the expectations linked to the term, through three films produced in different decades: The Red Cross girls by Rafael J. Salvia (1958); Women on the Verge of a Nervous Breakdown by Pedro Almodóvar (1988); and My life whith out you by Isabel Coixet (2003). Once the films had been viewed, 21 focus groups were organized, made up of between 3 and 5 women of different ages and, in order to analyze the experience, the 21 coordinators of the discussion groups were interviewed. The data obtained from the interviews and the focus groups were analyzed following a qualitative approach, through the technique of content analysis. The results show that feminist thought has had an impact on the lives of Spanish women, but in different ways depending on their age, thus, there is a discrepancy regarding the roles that women have to fulfill, a difference based on the difficulties they have had to face. With respect to the choice of film and the focus group as research techniques, it is possible to affirm that they have worked, since they have allowed women of three different generations to dialogue and review their approaches to the social construction of gender from a diachronic perspective, generating an empathetic discourse of acceptance and sisterhood, which implies, in spite of the discrepancies, the recognition of the difficulties of each generation of women.
History of scholarship and learning. The humanities, Social Sciences
Quadratization refers to a transformation of an arbitrary system of polynomial ordinary differential equations to a system with at most quadratic right-hand side. Such a transformation unveils new variables and model structures that facilitate model analysis, simulation, and control and offers a convenient parameterization for data-driven approaches. Quadratization techniques have found applications in diverse fields, including systems theory, fluid mechanics, chemical reaction modeling, and mathematical analysis. In this study, we focus on quadratizations that preserve the stability properties of the original model, specifically dissipativity at given equilibria. This preservation is desirable in many applications of quadratization including reachability analysis and synthetic biology. We establish the existence of dissipativity-preserving quadratizations, develop an algorithm for their computation, and demonstrate it in several case studies.
Mohammad Mehdi Pourhashem Kallehbasti, Mohammad Ghafari
Static program analysis development is a non-trivial and time-consuming task. We present a framework through which developers can define static program analyses in natural language. We show the application of this framework to identify cryptography misuses in Java programs, and we discuss how it facilitates static program analysis development for developers.