Search Results (311)

Achieving a credible net-zero transition requires reliable corporate environmental information to support effective climate governance. When firms overstate environmental commitments without corresponding improvements in actual performance, regulatory signals become distorted, and decarbonization efforts are weakened. This study examines whether stringent command-and-control environmental regulation enhances the credibility of corporate climate commitments. Using the staggered implementation of China’s Air Pollution Prevention and Control Action Plan as a quasi-natural experiment, we construct a firm-level measure of corporate greenwashing that captures the divergence between environmental discourse and regulatory performance. Based on a multi-period difference-in-differences model, the results indicate that environmental regulation significantly reduces corporate greenwashing, with the probability of inconsistency between environmental claims and actual behavior declining by approximately 25 percent relative to the sample mean. Mechanism analysis shows that this effect operates through increased green technological innovation and heightened public environmental concern, which together strengthen substantive compliance and external monitoring. The moderating analysis shows heterogeneous responses across firms: board independence strengthens the policy’s inhibitory effect, while market share and institutional ownership attenuate it. Overall, the findings suggest that command-and-control regulation improves the credibility of disclosure and reinforces the informational foundations necessary for an effective net-zero transition. Full article

The study reconsiders the architectural production associated with Russian Suprematism (which was speaking of “the supremacy of pure artistic sensation” rather than the veritable figurative depiction of real-life subjects) in the early Soviet period as a coherent and conceptually rigorous mode of speculative world-making rather than as a marginal or unrealized appendix to avant-garde art history and theory. By examining the architectural propositions articulated by Kazimir Malevich and then elaborated by his younger colleagues Lazar Khidekel, Ilya Chashnik, and Nikolai Suetin, the study advances the claim that Russian Suprematist architecture constituted an epistemic experiment aimed at redefining the very ontological premises of architecture. Far from functioning as a mere transposition of abstract pictorial language into three-dimensional form, Suprematist planits, architectons, and aerocentric projects operated as instruments for thinking spatiality beyond terrestrial gravity, anthropocentric utility, and historical typology. Situating these projects within the intellectual horizon of Russian cosmism and early aerospace thought, the article demonstrates how Suprematist architecture intersected with contemporary philosophical, scientific, and technological discourses that envisioned humanity’s active participation in the reorganization of cosmic space. The architectural imagination of Suprematism emerges here as inseparable from broader debates on excitation, non-objectivity, transformation of matter, and the reconfiguration of human corporeality. Through close analysis of formal strategies, pedagogical frameworks, and theoretical writings, the paper reveals the internal plurality of avant-garde Suprematist architectural inquiry, ranging from ecological proto-urbanism and hovering settlements to magnetic and cruciform spatial systems. Ultimately, the paper argues that the historical non-realization of these projects should not be interpreted as a failure but as an intrinsic feature of their speculative methodology. Suprematist architecture is thus redefined as an anticipatory practice whose unresolved propositions continue to resonate with contemporary discussions on space habitation, planetary design, ecological responsibility, and post-human architectural thought, challenging inherited assumptions about the scope and function of architecture as such. Full article

This study introduces a four-pillar student-activity framework (Studying and Learning, Research and Projects, Personal and Career Development, and Campus and Community Life) to analyze AI’s ethical challenges in higher education. Drawing on peer-reviewed sources from 2022 to 2025, we identify recurring risks across pillars: academic integrity, privacy/data protection, bias/fairness/equity, student agency/(de)skilling, and governance gaps. We distill three cross-pillar principles: disclosure plus process evidence (e.g., prompt/version logs), privacy-by-design, and proportionality and equity/fairness scaffolds (institutional access, bias audits, and multilingual support). These translate into actionable strategies for assessment redesign, research supervision, career services, and campus operations. The framework unifies fragmented discourse, supports institutional decision making, and reveals gaps for longitudinal and causal research. It demonstrates that responsible AI use emerges when processes are visible, data practices are proportionate, and access is equitable, amplifying human learning without eroding trust or integrity. Full article

Industry 5.0 (I5.0) reframes industrial transformation by placing human-centricity, sustainability, and resilience alongside digitalisation, and by linking the twin transition to circular economy ambitions. While the post-2020 literature is expanding, implications for Manufacturing Systems are presented as fragmented principles, technologies, or isolated use cases, which complicates traceability from I5.0 goals to system-level requirements. This manuscript addresses this gap by consolidating the I5.0 discourse via a challenge-based synthesis and translating it into Manufacturing System implications using an evidence-mapping logic. Reported challenges are clustered into four topic groups (planet and society, products and consumption, production, people) and mapped to the four Manufacturing System pillars to expose evidence concentrations and gaps. Building on this bridge, a Manufacturing Systems’ challenges taxonomy is derived in three streams: (i) personalised and circular products, (ii) sustainable, flexible, human-centric Manufacturing Systems, and (iii) an education and skills paradigm for reskilling across industry and research ecosystems. A research agenda matrix highlights priorities in lifecycle information infrastructures, orchestration metrics, human–automation symbiosis, and governance at a system-of-systems scale. In the coded corpus (n = 30), evidence is denser in Manufacturing Systems and operations and competitiveness and people (22 and 23 papers) than in materials and processes and product, tooling, and assembly (7 and 10 papers). Full article

Artificial Intelligence (AI) has transitioned from a specialized research area to a ubiquitous socio-technical infrastructure influencing sectors from healthcare and law to manufacturing and defense. In tandem with its transformative promise, AI has created an exponentially expanding ethics literature questioning, fairness, transparency, accountability, and justice. This review synthesizes publications and key policy developments between 2019 and 2025, bringing sectoral discourses together with cross-cutting frameworks. Grounded in a systematic scoping review methodology, we frame the field along four meta-dimensions: trust and transparency, bias and fairness, governance & regulation, and justice, while we investigate their expression across diverse sectors. Special attention is dedicated to healthcare (patient trust and algorithmic bias), education (integrity and authorship), media (misinformation), law (accountability), and the industrial sector (data integrity, intellectual property protection, and environmental safety). We ground abstract principles in concrete case studies to illustrate real-world harms and mitigation strategies. Furthermore, we incorporate pluralistic ethics (e.g., Ubuntu, Islamic perspectives), environmental ethics, and emerging challenges posed by Generative AI and neuro-AI interfaces. To bridge theory and practice, we propose an operational governance framework for organizations. We contend that success involves transitioning from principles toward ethics-by-design, pluralistic governance, sustainability, and adaptive oversight. This review is intended for scholars, practitioners, and policymakers who need a comprehensive and actionable framework for navigating the complex landscape of AI ethics. Full article

This article examines how artificial intelligence and algorithmic systems are reconfiguring truth regimes in digital societies, introducing the concept of “Artificial Truth” to describe an emerging form of epistemic governance where knowledge production and validation become infrastructural functions of sociotechnical systems. The study develops an integrated theoretical framework combining Foucault’s notion of truth regimes, Bourdieu’s theory of symbolic capital and fields, and Actor-Network Theory’s constructivist approach. Through conceptual analysis, the article investigates how algorithmic recommendation systems, generative AI, and automated fact-checking operate as epistemic devices that actively shape what is recognized as credible, authoritative, and true in public discourse. The analysis reveals three fundamental transformations: (1) the restructuring of trust economies, with epistemic authority shifting from institutional expertise to platform-native capital based on engagement metrics and affective proximity; (2) the emergence of generative AI as an epistemic actor producing “synthetic truth” through linguistic fluency rather than propositional understanding; (3) the institutionalization of computational veridiction in algorithmic fact-checking systems that translate situated epistemic judgments into probabilistic classifications presented as neutral. These dynamics configure a regime where truth is evaluated less by correspondence with reality and more by computational plausibility and platform integration. The article’s primary contribution lies in providing a unified theoretical framework for understanding contemporary transformations of epistemic authority, moving beyond disinformation studies to analyze AI as an epistemic actor. By integrating classical sociological perspectives with Science and Technology Studies, it conceptualizes algorithmic systems as epistemic infrastructures that embody specific power relations, restructure symbolic capital economies, and distribute epistemic authority asymmetrically, with profound implications for democratic knowledge, citizen epistemic agency, and public sphere pluralism. Full article

This review paper reviews research literature on Diamond Open Access (DOA) journals—sometimes also called Platinum Open Access—that was produced after this journal segment started to become a priority in European research policy around 2020. It contextualizes the current science policy debate, critically examines different understandings of DOA, and reviews studies on the role of such journals in scholarly communication. Most existing research consists of quantitative studies focusing on aspects such as the number of DOA journals, their publication output, the diversity of the landscape in terms of subject areas, languages, publishing entities, indexing in major databases, awareness and perception among scholars, cost analyses, as well as insights into the internal operations of DOA journals. The review shows that research on DOA journals is partly influenced by the science policy discourse in at least two ways: first, through the normativity inherent in that discourse, and second, through the temporality of policy-driven research of practical relevance, which leaves important aspects of the phenomenon understudied. Moreover, research on the DOA journal landscape has implications beyond understanding this particular journal segment, as it also challenges established views of the global system of scholarly communication. Full article

During elections, information manipulation on social media has accelerated the use of artificial intelligence, yet the evidence is difficult to interpret without an integrated view of methods, data, and evaluation. We mapped 557 English-language journal articles from Scopus and Web of Science, combining performance indicators, science mapping, and a focused full-text synthesis of highly cited papers. The literature grows sharply after 2019, peaks in 2025, and shows geographically uneven production, with collaboration structured around a small set of hubs. The thematic structure suggests that, during the pandemic era, infodemic-related research served as a catalyst, intensifying scientific attention to fake news and disinformation and expanding the associated detection and monitoring agendas. In addition, socio-political harm constructs such as hate speech, extremism, and polarization appear as recurrent and structurally central targets, highlighting that election-relevant work often extends beyond veracity assessment toward monitoring discourse risks. Blockchain also emerges as a novel and adjacent integrity theme, aligned with authenticity and provenance-oriented mitigation rather than mainstream detection pipelines. AI for electoral disinformation is not reducible to veracity classification, as influential studies also target automation and coordinated behavior, verification support, diffusion analysis, and estimation frameworks that focus on exposure and impact. Evaluation remains heterogeneous and is often shaped by benchmark settings, making high accuracy values hard to compare and potentially misleading when labeling quality, topic leakage, or context shift are not characterized. Overall, the findings motivate evaluation protocols that align operational objectives with modeling roles and explicitly address robustness to temporal and platform changes, asymmetric error costs during election windows, and representativeness across electoral contexts and languages, while also guiding future work on emerging integrity challenges and governance-relevant deployment settings. Full article

Intimate partner violence (IPV) remains understudied in China despite its public health significance. Previous research lacks comprehensive analysis of how Chinese media frames this issue, creating a gap in understanding the sociocultural factors shaping public discourse. This study employs corpus-based framing analysis of 603 news articles (435,581 words) from major Chinese newspapers spanning 2012–2022, a period encompassing significant legal developments including the 2016 Domestic Violence Law. We analyze how IPV is framed through examination of keyword frequencies, collocation patterns, and concordance analysis. Our findings reveal that IPV is predominantly framed as matrimonial conflict and family dispute rather than criminal violence requiring state intervention. We argue that framing IPV as a ‘family issue’ operates as a spatial containment strategy, relocating violence to the domestic sphere while rerouting intervention into administrative/civil channels rather than criminal accountability spaces. Our findings reveal significant imbalances in stakeholder representation, with government and legal voices dominating the public discourse domain while community support organizations are marginalized. Source attribution patterns produce uneven zones of legitimacy, where state actors occupy authorized public space while survivors’ experiences remain confined to private, silenced domains. This research enhances the understanding of IPV media coverage in China while highlighting the need for more inclusive public discourse. Full article

This study empirically investigates how Environmental, Social, and Governance (ESG) discourses among major Korean Business-to-Business (B2B) corporations (POSCO, LG Chem, and HD Hyundai) were reconfigured in the context of former President Trump’s re-election campaign and the 2024 U.S. presidential election. The observation periods were divided into the Pre-Trump period (1 May 2023 to 30 April 2024) and the Post-Trump period (1 May 2024 to 30 April 2025). External discourses were examined using social media, news, and blog posts, while internal discourses were analyzed through the CEO’s New Year addresses from 2021 to 2025. Keyword frequency analysis and co-occurrence network analysis, conducted via the ‘Sometrend’ platform, were combined to trace structural transitions in corporate discourses. The results show that: (1) the relative share and network centrality of environmental (E) keywords declined in the Post-Trump period, with several environmental terms losing core positions and becoming peripheral or bridging nodes, while policy- and economic-related terms increased; (2) social (S) and governance (G) keywords appeared only sporadically and remained peripheral across periods; (3) temporal concentrations of policy–economic keywords coincided with significant political and market-related events, such as financial volatility in 2023 and the tariff policy announcement in February 2025, indicating temporal alignment rather than deterministic causality; (4) firm-level differences were evident: POSCO exhibited the most pronounced structural shift, LG Chem’s discourses increasingly emphasized supply chain and investment-related terms alongside environmental keywords, and HD Hyundai showed a shift toward more risk- and operation-oriented keywords in the later period; and (5) CEO New Year addresses displayed directionally consistent patterns with external discourse, supporting cross-textual alignment. These findings demonstrate that ESG discourse is not a fixed normative language but a strategically adaptive frame that varies according to political–economic contexts and industrial conditions. The relative weakening of the environmental frame in terms of discourse centrality, alongside the strengthening of the policy–economic frame, differed by industry, reflecting variations in regulatory exposure and operational characteristics. By observing ESG discourses longitudinally and comparatively, this study provides empirical evidence of how political and industrial dynamics reshape corporate discourses and CEO communication. Moreover, keyword frequency and co-occurrence network analysis are validated as effective methods for identifying discourse shifts, offering both academic contributions and practical implications for corporate communication analysis. Full article

The goal of the article is to demonstrate the common threads and methods of studying digital storytelling as a unified, second-order aesthetic code. Just as the category of translation, when applied to digital literature, was expanded into a more complex set of methods known as media translation, the article applies similar logic to the notion of intertextuality and proposes an augmented form of “digital“ or “media intertextuality“. Games, interactive fiction, hypertext fiction, story generators, and other born-digital forms are all “texts” that share evolutionary poetics and intertextual strategies extending beyond language into multimodal, procedural, and embodied affordances. Drawing on the concept of structural quotation and semiotic calques, this article suggests that intertextuality should operate across multiple extra-linguistic registers: visual, procedural, and embodied. Neither evolutionary continuity nor broad intertextuality have been sufficiently emphasized in current game studies outside the literary angle. In several examples and case studies—from Zork II to World of Warcraft—this paper demonstrates how repetition with difference, brought about by intertextual links, generates evolutionary continuity and intertextual richness. In this dialogical ecology, AAA blockbusters and experimental works are worth studying together, even if, within the discourse of digital entertainment, they are currently at war. The former push the boundaries of expressive possibility, whereas the latter accrue cultural capital by reworking and critiquing shared codes. Full article

Social media has become a vital source for humanitarian organizations to gather information during crises. However, existing multimodal classification methods operate primarily as isolated systems, while neglecting external references crucial for accurate judgment. Furthermore, while user comments can provide valuable context, they are often scarce during the early stages of a crisis. To address these limitations, we propose a framework named Mix-Persona Comment Generation with Geographically Enhanced Context Retrieval for LLM Instruction Fine-tuning (MPCG-GECR). To mitigate comment scarcity, we employ a Synthetic Persona Generator (SPG) that prompts LLMs to adopt diverse mix-personas, generating synthetic comments that simulate multi-perspective public discourse. To incorporate external references, we introduce a Geographically Enhanced Context Retrieval (GECR) module. Unlike standard retrieval approaches, GECR utilizes a hybrid re-ranking strategy to identify samples that are both multimodally similar and geographically consistent, serving as reliable reference anchors for the LLM. By integrating these social perspectives and geographic references into a unified instruction-tuning format, we transform the classification task into a context-aware text generation problem and fine-tune the LLM using Low-Rank Adaptation (LoRA). Extensive experiments on the CrisisMMD and DMD datasets demonstrate that MPCG-GECR effectively overcomes data scarcity and context isolation, significantly outperforming existing methods. Full article

This study explores how digital media ecosystems shape collective visions of the future under conditions of rapid technological innovation and the growing influence of artificial intelligence (AI). Drawing on a large corpus of social media content comprising 50,036,592 tokens, the research examines institutional narratives and user-generated responses through a hybrid methodological framework. This framework combines information-wave detection, network analysis, semantic and associative modeling (TextAnalyst 2.32), and interpretation supported by a large language model (GPT-5). The methodological contribution of the study lies in the integration of network-based and semantic algorithms with AI-driven analytical tools for the examination of large-scale textual data. The findings indicate that media discourses about the future operate as key mechanisms through which societies interpret the environmental, social, and economic consequences of technological change. Institutional actors promote multiple future-oriented models that often conflict with one another at both discursive and practical levels. In contrast, user-generated content reflects widespread fear, skepticism, and distrust. Prominent themes include nostalgia for the past, anxiety about socio-economic and environmental consequences, and concerns related to expanding forms of digital control. The analysis also reveals divergent perspectives on urban development. Positive narratives emphasize ecological balance, a comfortable urban environment, thoughtfully designed mixed-use development, and solutions to transportation challenges. Negative narratives, by contrast, focus on over-densification, environmental degradation, and the erosion of privacy in technologically saturated urban spaces. Full article

The rapid rise in the use of Liquefied Petroleum Gas (LPG) as an alternative vehicle fuel in Ghana presents both opportunities and risks within the national energy transition agenda. This study investigates LPG safety as well as environmental and regulatory implications using a multi-method quantitative approach that combines structured survey data, exploratory multivariate analysis (MCA), and machine learning classification (Random Forest) to uncover emerging associations and patterns in LPG safety practices. Primary data were obtained from 384 respondents, including vehicle operators, auto-technicians, regulatory officials, and LPG station attendants across five major transport zones: Kejetia, Asafo, Ahodwo, Bantama, and Suame Magazine. The MCA identified four distinct behavioural and safety profiles—At-Risk, Proactive Safety, Compliant and Equipped, and Formal and Reported—reflecting diverse compliance and risk patterns across socio-occupational groups. The Random Forest classifier achieved a predictive accuracy of 96.5% based on cross-validated performance. Sensitivity and specificity values were high, indicating reliable discrimination among incident types. To reduce the risk of overfitting, k-fold cross-validation and monitored error convergence were performed across increasing numbers of trees. While the model shows strong predictive capability, we present these results cautiously and emphasize observed associations and emerging patterns rather than definitive predictive conclusions. The findings reveal that while economic motivations underpin LPG adoption, weak institutional enforcement and widespread informal installations heighten safety vulnerabilities. Comparisons with sub-Saharan and Asian contexts underscore the need for a structured regulatory framework, mandatory certification of installers, and periodic vehicle inspections. The study contributes to the broader discourse on informal energy transitions in developing economies by demonstrating how technical and behavioural determinants interact within weak regulatory systems. Policy recommendations emphasize the integration of data-driven risk assessment tools into regulatory oversight to enhance vehicular LPG safety and sustainability. Full article

Background: The humanization of care is increasingly recognized as a core component of healthcare quality; however, its meaning remains complex and strongly shaped by organizational, professional, and educational contexts. Nursing students, as future healthcare professionals, play a crucial role in the development and transmission of humanized care values, making their representations of the humanized hospital particularly relevant for understanding how these values are constructed during professional education. Aim: To explore how undergraduate nursing students conceptualize the humanized hospital. Methods: A qualitative exploratory study was conducted involving 742 undergraduate nursing students enrolled in a Bachelor of Science in Nursing program in Italy. Data were collected through a single open-ended written question inviting students to describe how they imagine a humanized hospital. Textual data were analyzed using Automatic Analysis of Textual Data within an Exploratory Multidimensional Data Analysis framework, enabling the identification of shared lexical patterns, discursive clusters, and latent semantic dimensions within a large textual corpus. Findings: Students articulated the humanized hospital as an integrated and system-oriented care environment in which relational, organizational, professional, and holistic dimensions are deeply interconnected. Humanization was associated not only with empathy, respect, and emotional engagement, but also with organizational functioning, teamwork, adequate resources, and professional competence. Two latent dimensions structured these representations: the first highlighted organizational systems as enabling conditions for person-centered care, while the second framed professional operability and technical competence as foundations for a holistic understanding of patients’ physical, psychological, and social well-being. Conclusions: Undergraduate nursing students’ discourse revealed an articulated and multidimensional representation of hospital humanization, conceptualizing it as an emergent property of healthcare environments rather than as a function of individual attitudes alone. These findings underscore the importance of addressing hospital humanization simultaneously at relational, educational, and organizational levels and highlight the need for nursing education programs and healthcare institutions to foster structural and professional conditions that sustainably support humanized care in clinical practice. Full article