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The Dark Five - statistical anomaly or persistent phenomena: An exploratory investigation into the factor structure of the SD4 in multiple samples
Full text linkThe existence of a Dark 5 (D5-SD4) within the Short Dark Tetrad Scale (Paulhus et al., 2021) was proposed tentatively by Crawford et al. (2025). However, extensive replication is required to determine if the D5-SD4 factor structure is a persistent phenomenon or a statistical artefact of the single data source used. The present study sought to explore if a D5-SD4, rather than the SD4 dimensional representation would fit the data better in several populations worldwide. In total, 12 samples from 11 different countries, with 7157 participants were analysed. The results of multivariance analysis, alignment optimization procedure and comparative confirmatory factor analysis demonstrate that D5-SD4 constantly exhibits better fit than four-factor model, albeit the differences in indices values vary across the samples. Alignment analysis showed that group means could be meaningfully compared across groups. Future research should investigate the discriminative utility of the new model
Generative AI in Curriculum Design: Advancing or Undermining Decolonisation Efforts?
No full textThe integration of generative artificial intelligence (AI) into curriculum design presents a paradox for educational decolonisation. This chapter examines AI’s dual potential to either advance or undermine these critical efforts. On one hand, AI offers transformative opportunities to create inclusive, culturally relevant materials by embedding diverse perspectives and representing Indigenous knowledge systems. It can personalise learning for marginalised students, helping to dismantle the Eurocentric focus of traditional curricula. Conversely, uncritical adoption poses significant threats. AI systems, predominantly trained on data from the Global North, risk perpetuating colonial biases and reinforcing hegemonic narratives. This can lead to the exclusion of marginalised voices and what has been termed “algorithmic colonialism”. Balancing these tensions requires a proactive, principled framework. This chapter advocates for the ethical implementation of AI through the co-development of culturally sensitive tools, fostering critical AI literacy, and establishing robust, inclusive governance to ensure technology serves epistemic justice
The Prospective Developments of Artificial Intelligence in the Domain of Knowledge Management: Challenges and Opportunities
No full textAs organisations increasingly embrace digital transformation, Artificial Intelligence (AI) is poised to revolutionize Knowledge Management (KM). This chapter explores the evolving role of AI in KM, analysing the transformative potential of AI technologies like machine learning, natural language processing, and automation in enhancing the creation, sharing, and utilisation of knowledge within organisations. The chapter also delves into the challenges businesses face when integrating AI into KM systems, as well as the opportunities that AI presents to streamline processes, drive innovation, and enable smarter decision-making. The chapter will address both the technical and human aspects of AI in KM, proposing strategies to maximize AI's benefits while mitigating risks such as data privacy concerns, algorithmic biases, and resistance to change. By synthesising current trends and future projections, the chapter will provide insights into how AI can shape the future of Knowledge Management across industries
The CARE model: A research tool for understanding resilience.
No full textAbstract
Healthcare organisations are complex, dynamic systems where resilience—the ability to adapt to misalignments between demand and capacity—is critical but difficult to define and study. This chapter introduces the CARE (Concepts for Applying Resilience Engineering) model, a theoretical framework developed to make resilience visible and measurable in healthcare contexts. Initially conceptualised as the relationship between misalignments and staff adaptations, the CARE model has evolved through empirical application across various healthcare settings, resulting in CARE 2.0 and 3.0. These iterations introduced categorisations of misalignments and adaptations, enabling more systematic analysis and cross-setting comparisons. The model provides a structured yet flexible approach to understanding resilience, emphasising the need to examine work as done rather than relying solely on outcomes to infer resilience. By offering a practical tool for both research and quality improvement, the CARE model contributes significantly to advancing resilience engineering in healthcare and promoting safer, more adaptable systems
Transforming Knowledge Management through Synergistic AI-Human Collaboration
No full textAs organisations increasingly navigate the complexities of the digital age, the incorporation of Artificial Intelligence (AI) into knowledge management (KM) frameworks is becoming indispensable for the attainment of sustained competitive advantage. This chapter explores the transformative capabilities of AI within KM, underscoring the pivotal significance of human-AI collaboration. We will investigate how emerging technologies, including AI, machine learning (ML) and natural language processing (NLP), can enhance key KM dimensions: the creation, storage, retrieval, sharing, and application of knowledge. Furthermore, the chapter considers the essential contributions of human expertise, contextual understanding, and decision-making in KM practices. By elucidating the synergy between the advantages of AI, like scalability, data analysis, human competencies, creativity and empathy, the chapter further explores specific implementations of AI-human collaboration, encompassing automated knowledge repositories for knowledge generation, NLP for knowledge retrieval, and tailored recommendations for knowledge application. We will also address the ethical challenges and implications that accompany AI integration, focusing on issues such as bias, the need for transparency, trust in AI systems, data privacy, and the balance between human oversight and AI control. Finally, we outline practical implications for organizations aiming to empower talent, create AI-friendly infrastructures, and streamline knowledge processes to foster successful human-AI partnerships. We conclude by discussing the future of AI-human collaboration in KM, identifying emerging trends and the long-term benefits of integrating AI into organisational learning and innovation
Immersive simulation in healthcare education: a systematic review
No full textBackground:
Fully immersive simulation environments can be created using 360° projectors to project images or videos onto the walls of a room or ‘cave’; they are a novel way to scaffold learning and increase student performance and competence.
Aims:
This study aims to investigate the use of immersive 360° simulation in preregistration education.
Methods:
A literature search was carried out and PRISMA guidelines followed; seven papers were reviewed in full.
Findings:
Thematic analysis found three clear themes: readiness for practice; realism; and a safe environment.
Conclusion:
Immersive simulation has a positive effect on healthcare education, improving student competence, confidence and readiness for practice, and providing realistic experiences within a safe and supportive environment. It allows students to engage in complex, realistic scenarios that bridge the theory-practice gap, enhancing their critical thinking, clinical judgement and interprofessional skills. This learning method has particular relevance to paramedic education. Research is recommended to explore the long-term effects and potential improvements
The Rise of Non-consensual Policing in the United Kingdom
No full textThis chapter discusses the contentious rise of non-consensual policing in the UK due to the harsh social and financial effects of politically imposed and its unintended effect of eroding the faith and trust of the British public in the police service. The social and financial effects include the 2008 global financial crash which led to the so-called age of austerity, ‘Brexit’, the ruinous COVID-19 pandemic which all contributed to annual cuts to the policing and criminal justice budget as well as the closure of police stations, the loss of officers and the deskilling of the police role. We argue that the hallowed British model of policing, ‘policing by consent,’ is in grave danger of being altered irrevocably. ‘Consensuality’ (public consent) is enshrined in the creation of modern, democratic policing which evolved from the creation of the Metropolitan Police in 1829 by Sir Robert Peel. This formed the basis of the professionalisation of modern policing as we know it and became the gold standard for policing in the UK. Using anecdotal evidence from our own experiences and observations, we lay out the main argument using two in-depth case studies: (1) the death of consent in England and Wales and (2) the rise of non-consensual policing in Scotland. We justify using anecdotal evidence because the issues are so contemporary that they have not been properly aired or interrogated thoroughly in academic policing journals. We argue that the death of policing by consent is not inevitable but that the government, politicians and policymakers must take immediate action to end the rise of non-consensual policing in the UK before it is too late
Sitting, seeing, and getting lost: the sensory aesthetics of Latvia’s women’s prison
No full textThis chapter delves into what imprisonment feels like in the global east, with a particular focus on the first encounter with the prison as an institution of confinement. The central claim of this chapter is that by focusing on women’s sensory experience of imprisonment at the start of their sentence, a better understanding can be gathered about carceral power, which in the global east is a relational and symbolic one rather than a physical manifestation in space. The spatial and cultural ‘carceral collectivism’ facilitates an intimacy in the sensorial spectrum of surveillance that essentially provides both control and support functions
Global Perspectives on Generative AI in Higher Education: Comparative Analysis of Ethical Adoption, Policy, and Stakeholder Roles
No full textThe swift incorporation of generative AI (GenAI) technologies into higher education has ignited considerable discussion regarding their ethical implications across various global contexts. This chapter presents a comparative analysis of how different regions and educational systems are adopting GenAI tools, including automated content generation, personalised learning platforms, and AI-supported research assistance. By analysing case studies from North America, Europe, Asia, and Africa, the chapter delves into both the advantages and obstacles posed by these technologies. Crucial ethical issues such as data privacy, academic integrity, bias, accessibility, and the risk of AI-induced inequality are scrutinised within the framework of local cultural, legal, and policy environments. Additionally, the chapter addresses the implications for educators, students, and institutional governance, highlighting the importance of globally informed ethical standards and regulatory frameworks to facilitate responsible AI integration in higher education. By providing a nuanced perspective on these international viewpoints, the chapter seeks to offer meaningful insights for policymakers, educators, and researchers who are navigating the intricate landscape of AI ethics in academia
Controversial motherhood on the football field: a cross-analysis between France and England
Full text linkHigh-level women’s football highlights the ongoing feminist struggle for freedom of choice regarding motherhood and work-life balance. Inadequate institutional policies in football contribute to the invisibility of pregnancy, rendering it “abnormal”. The risk of losing their job or fear of discrimination pushes female football players to delay or abandon their plans for motherhood. Far from being a simple individual choice, implicit and explicit pressures underlie this decision, making motherhood a new battleground for the recognition of female athletes. This article illustrates the shared experiences of players in France and England in relation to the perception and treatment of pregnancy, and how these perpetuate gender inequalities and norms related to parenthood
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