This article examines multi-modal self-defence actions in personal safety training classes for girls and women. The actions have linguistic and embodied components. An example is shouting “back off” at an imagined attacker while assuming a self-defensive stance position. An additional distinctive aspect of the phenomenon of interest is that it is done collectively as a multi-person party. Our work builds on and extends prior research in multimodal conversation analysis which has shown the ways language and bodily actions fit together. Using a collection of 200 cases drawn from more than 50 hours of video footage, two broad kinds of recurrent practices are described the support the class to achieve the collective, co-production of multi-modal self-defence actions. One is the projective, embodied syntactic structures instructors use to demonstrate the action and co-ordinate its execution. The other is the grammar of the verbal component that scaffolds the timing of physical techniques, especially ones where there is a combination of moves. By examining how linguistic and embodied components of multi-modal self-defence actions are brought together and done by multiple participants at the same time, we find empirical support for the innovative theoretical idea that syntax can be emergent and embodied rather than predominantly hierarchical and psycholinguistic. Data is in New Zealand English.

The valuation of the benefits to humans of ecosystem services (ESs) provided by nature has become increasingly important. A current challenge is the measurement of the range of benefits which are not traded in the marketplace and are generally considered intangible, with further challenges to even classify them formally, e.g., as cultural ecosystem services (CESs). Previous studies have emphasized a related challenge: the strong need for engagement of not just experts but ’ordinary people’. Approaches using participatory approaches and less formal communication pathways to draw out local CES values have been reported. However, critical reflections of those studies reported significant differences in understanding between ’outsider researchers’ and ’locals’, calling validity deeply into question. Even deliberative approaches backfired by significantly modifying local social constructs during elicitation. In this study, we demonstrate a fundamentally different kind of approach, developed from the bottom–up sustainability indicator development process called WeValue InSitu. It focuses not on improving deeper top–down ‘engagement’ of a specific topic, but instead on improving local articulation of existing envelopes of in situ human shared values, naturally integrated. The WeValue InSitu output is a framework of separate but interlinked concise Statements of local shared values. Some of these Statements may refer to values concerning ecosystems, but situated amongst others. Here, we analyze the outputs from 23 convenience groups in three sites in Nigeria and investigate the shared values found empirically against existing economics-based MEA classifications. The findings include hybrid values which span existing CES sub-categories and even across into market-based categories. This opens a discussion as to whether future ES valuation frameworks might evolve more usefully with foundations built on empirically derived typologies of human values, rather than bolt-on modifications to financially based economics concepts. It also raises questions about the validity of current valuations made which cannot capture empirically found human values.

To take advantage of the full range of services that online social networks (OSNs) offer, people commonly open several accounts on diverse OSNs where they leave lots of different types of profile information. The integration of these pieces of information from various sources can be achieved by identifying individuals across social networks. In this article, we address the problem of user identification by treating it as a classification task. Relying on common public attributes available through the official application programming interface (API) of social networks, we propose different methods for building negative instances that go beyond usual random selection so as to investigate the effectiveness of each method in training the classifier. Two test sets with different levels of discrimination are set up to evaluate the robustness of our different classifiers. The effectiveness of the approach is measured in real conditions by matching profiles gathered from Google+, Facebook and Twitter.

To face the new challenge of giving an all-around picture of people's online behavior, in this paper we perform a multidimensional analysis of users across multiple social media sites. Our study relies on a new rich dataset collecting information about how users post their favorite contents and about their centrality on different social media. Specifically posting activities and social sites usage have been gathered from the social media aggregator Alternion. The analysis of social media usage shows that Alternion data capture the typical trend of today's users. However the novelty is the multidimensional and longitudinal nature of the dataset. In fact by performing a rank correlation analysis on the degree in the different social sites, we find that the degrees of a given user are scarcely correlated. This is suggesting that the individuals' importance changes from medium to medium.We also investigate the posting activities finding a slightly positive correlation on how often users publish on different social media. Finally we show that users tend to use similar usernames to keep their identifiability across social sites.

The continual launches of new online social media that meet the most varied people’s needs are resulting in a simultaneous adoption of different social platforms. As a consequence people are pushed to handle their identity across multiple platforms. However, due the to specialization of the services, people’s identity and behavior are often partial, incomplete and scattered in different “places”. To overcome this identity fragmentation and to give an all-around picture of people’s online behavior, in this paper we perform a multidimensional analysis of users across multiple social media sites. Our study relies on a new rich dataset collecting information about how and when users post their favorite contents, about their centrality on different social media and about the choice of their username. Specifically we gathered the posting activities and social sites usage from Alternion, a social media aggregator. The analysis of social media usage shows that Alternion data reflect the novel trend of today’s users of branching out into different social platforms. However the novelty is the multidimensional and longitudinal nature of the dataset. Having at our disposal users’ degree in five different social networks, we performed a rank correlation analysis on users’ degree centrality and we find that the degrees of a given user are scarcely correlated. This is suggesting that the individuals’ importance changes from medium to medium. The longitudinal nature of the dataset has been exploited to investigate the posting activity. We find a slightly positive correlation on how often users publish on different social media and we confirm the burstiness of the posting activities extending it to multidimensional time-series. Finally we show that users tend to use similar usernames to keep their identifiability across social sites.

Objectives To explore the barriers to conversations about deceased organ donation among adults living in the UK. Design Systematic review with narrative synthesis. Data sources PubMed, MEDline via OVID, APA PsycInfo via EBSCO, Web of Science via Clarivate and Scopus via Elsevier, covering studies that were published between January 2006 and December 2023. Searches were conducted on 1 December 2023 and completed on 2 February 2024. Eligibility criteria Studies published between January 2006 and December 2023, focusing on barriers to organ donation conversations among adults in the UK. Both qualitative and quantitative studies were included, emphasising cultural and generational factors. Non-English studies and those unrelated to the UK were excluded. Data extraction and synthesis Screening and data extraction were conducted by two independent reviewers using a standardised tool. Quality assessment was performed using Joanna Briggs Institute checklists, evaluating study bias. A narrative synthesis approach was used to integrate findings from heterogeneous studies. Results 11 studies (6 qualitative, 5 quantitative) with a total of 4991 participants were included. Four main thematic barriers emerged: (1) jinx factor—cultural beliefs associating discussion of death with bad luck; (2) generational impact—younger people were more open but cautious of upsetting parents; (3) ethnic disparities in conversations—varied challenges across diverse backgrounds and (4) cues to action—media and personal experiences prompted conversations. Facilitators included culturally tailored communication and community engagement. Conclusion Conversations about death and organ donation are often brief and hindered by cultural taboos surrounding death, generational differences in attitudes and the influence of family dynamics. Further research is needed to understand communication patterns better and to tailor interventions that encourage open discussions about organ donation across different ethnic groups.

This research fills a knowledge gap by introducing a new conceptualization of digital transformation through a multidimensional digital transforming capability. It further examines the influence of four cultural types on this capability and its subsequent impact on product innovation. Empirical findings reveal that adhocracy, followed in descending order of influence by clan, market, and hierarchy cultures, is positively related to digital transforming capability, which in turn is positively related to product innovation in terms of new product newness, meaningfulness, and performance. Additionally, new product newness and meaningfulness each positively mediate the effect of digital transforming capability on new product performance.

From a Confucian perspective, critique serves as a tool for jiaohua (cultivation), encompassing not only the transmission of knowledge but also the cultivation of morality. This article adopts theoretical and empirical approaches to explore the Confucian understanding of critique. Theoretically, critique in Confucianism is not merely a challenge directed at external individuals or society; rather, it is viewed as a personal moral and social responsibility. Empirically, this article draws on fieldwork conducted in Confucian schools to demonstrate how students, teachers, and parents employ critique as a corrective tool in educational practice. Confucian critique challenges the monolithic framework of Euro-American critical traditions, offering a pathway of ‘multiple modernities’ to global higher education while addressing the pressing need for a more equitable and diverse knowledge production system.

The implementation of evidence-based practice (EBP) in nursing is essential for improving patient care outcomes, yet systemic barriers, leadership challenges, and resource limitations continue to hinder its integration into clinical practice. Nurse managers (NMs) play a crucial role in bridging the gap between policy directives and frontline implementation, yet the dynamic interplay between leadership strategies, knowledge utilisation, and organisational barriers remains underexplored, particularly in resource-constrained settings. This study examines how NMs navigate these challenges to sustain EBP adoption in acute care environments. This collective case study employed a longitudinal qualitative design across two acute care settings in the UK. Data were collected over eight months through semi-structured interviews with NMs, nonparticipant observations, and document analysis of clinical guidelines and internal reports. A thematic analysis approach was used to synthesise findings and provide a nuanced understanding of leadership strategies and systemic factors influencing EBP adoption. Six interconnected themes emerged: (1) Adaptive leadership strategies, where NMs employ a hybrid of directive and collaborative leadership approaches to drive EBP; (2) Overcoming organisational and resource barriers, including staff shortages, financial constraints, and competing priorities; (3) Knowledge utilisation and learning networks, highlighting the role of informal mentorship, structured CPD, and peer learning in sustaining EBP; (4) Digital transformation and EBP, examining the benefits and challenges of integrating digital tools and addressing IT literacy gaps; (5) Patient-centred adaptations, exploring how NMs balance evidence-based interventions with patient preferences and cultural considerations; and (6) Emotional and psychological support, underscoring the importance of managing staff resistance and mitigating change fatigue. Findings of this study emphasise the pivotal role of NMs in driving EBP implementation through adaptive leadership, strategic resource management, and fostering learning networks. Addressing organisational barriers requires multi-level interventions that integrate leadership actions with systemic enablers to promote sustainable, evidence-informed nursing practice. Findings provide critical insights for healthcare policymakers, hospital administrators, and educators in enhancing EBP uptake within resource-limited settings.

Discussion about the replacement of intellectual human labour by ``thinking machines'' has been present in the public and expert discourse since the creation of Artificial Intelligence (AI) as an idea and terminology since the middle of the twentieth century. Until recently, it was more of a hypothetical concern. However, in recent years, with the rise of Generative AI, especially Large Language Models (LLM), and particularly with the widespread popularity of the ChatGPT model, that concern became practical. Many domains of human intellectual labour have to adapt to the new AI tools that give humans new functionality and opportunity, but also question the viability and necessity of some human work that used to be considered intellectual yet has now become an easily automatable commodity. Education, unexpectedly, has now become burdened by an especially crucial role of charting long-range strategies for discovering viable human skills that would guarantee their place in the world of the ubiquitous use of AI in the intellectual sphere. We highlight weaknesses of the current AI and, especially, of its LLM-based core, show that root causes of LLMs' weaknesses are unfixable by the current technologies, and propose directions in the constructivist paradigm for the changes in Education that ensure long-term advantages of humans over AI tools.