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‘On the perimeter and fringe of war’: Norman Nicholson, Rural Modernity and Wartime
Get PDFThe author Norman Nicholson is an exemplary writer of rural modernity, acutely conscious of the need for rural areas to remain ‘living and organic communities’, as he puts it in his topographic book Greater Lakeland (1969). Here, I argue that his position in his lifetime home of Millom, an industrial town on the periphery of the tourist Lake District, gives his writing a unique, revisionary perspective on both modern/ist and war poetry: he is a non-combatant rural poet who focuses not on contested ground overseas, but on the rural and wartime industry on the north-western English coast. Born in 1914, his life was profoundly shaped by war, and while not often considered in these terms, he was inspired by modernist poetry, particularly that of his editor at Faber & Faber, T.S. Eliot. Reading Nicholson’s early writings ‘on the perimeter and fringe of war’ (‘Waiting for Spring, 1943’) during the Second World War, engaging with his editing, periodical contributions, and early poetry up to and including his debut collection Five Rivers (1944), enables us to see the multiple ways that the traces of war in his poetry have previously gone unrecognised, displaced, by the widely-theorised struggle of both combatants and civilians to articulate the experience of war, into dates, locations, events and depictions of the body. I conclude by examining Nicholson’s response to war after the Second World War, and commenting on the implications for more general theories of wartime
An Evolving Landscape of the Psychology of Judgment and Decision-Making: A Bibliometric Analysis
Get PDFAs a discipline with an expansive and intricate landscape, the field of judgment and decision-making (JDM) has evolved significantly since the beginning of the 2020s. The extensive and intricate nature of this field might pose challenges for scholars and researchers in designing course content and curricula as well as in defining research boundaries. Several techniques from a bibliometric study, such as co-word analysis and co-citation analysis, can provide insights into the scopes and directions of the field. Previous bibliometric studies on the psychology of JDM have primarily analyzed published documents restricted either by content areas or by journal outlets. The present study attempts to analyze a collection of published documents with broad search terms (i.e., “judgment*” or “decision mak*”) within the purview of the psychology subject area, separately by years of publication (from 2020 to 2022) using the bibliometrix package in the R environment. The most relevant journals and the most frequent keywords have suggested established areas of study, uncovering common themes, patterns, and trends. Beyond that, two science mapping techniques (i.e., keyword co-occurrence network and reference co-citation network) revealed 12 prominent themes that cut across the three-year period. These themes, alongside other intellectually stimulating issues, were discussed based on a comparison with outstanding book chapters and reviews. Implications for pedagogical purposes were also provided with a handful of notable resources
Why Do So Few Preliminary Questions Come From Czechia?
Get PDFAlthough a substantial part of the body of laws of an EU Member State is founded upon European Union law and norms, the number of preliminary questions emanating from courts in the Czech Republic appears to be disproportionately low compared to other similar EU Member States. The aim of this article is to analyse and outline possible reasons for the lack of preliminary questions coming from the Czech Republic. In her analysis, the author identifies three possible factors underpinning the issue. These factors include attitudes towards the EU and a general lack of understanding of the relevance of EU laws and norms; the role of preliminary rulings; and the perception and recognition of courts. An integral part of this analysis is a critical commentary on the shifts in how courts and tribunals are perceived within the meaning of Art. 267 TFEU. Lastly, the author offers guidance to fellow legal professionals and academics for interpreting EU norms
A multi-actor perspective of humanised midwifery care excellence: An exploratory survey
Get PDFHumanised midwifery care is a fundamental human right and need. This exploratory online survey presents a collective perception of meaningful standards of humanised midwifery care for excellent daily practice obtained from an international multi-actor group of maternity service users and providers. After performing a literature review, 137 key elements of humanised midwifery were extracted, listed, and rephrased into criteria. The criteria were distributed, and participants added 38 criteria. The perceived level of humanised midwifery performance was scored from 1 (low/substandard) to 10 (excellent). The 9–10 scores benchmarked humanised midwifery care excellence. 312 care professionals benchmarked 42 criteria, and 277 pregnant and postpartum women benchmarked 23 criteria showing a 30 % overlap. A total set of 50 criteria emerged, promoting humanised midwifery excellence. The benchmarking criteria suggest a shared conceptual thinking of person-centeredness and meaningfulness and provide a practical paradigm for the provision and receipt of humanised midwifery care
A Survey on Event Tracking in Social Media Data Streams
Get PDFSocial networks are inevitable parts of our daily life, where an unprecedented amount of complex data corresponding to a diverse range of applications are generated. As such, it is imperative to conduct research on social events and patterns from the perspectives of conventional sociology to optimize services that originate from social networks. Event tracking in social networks finds various applications, such as network security and societal governance, which involves analyzing data generated by user groups on social networks in real time. Moreover, as deep learning techniques continue to advance and make important breakthroughs in various fields, researchers are using this technology to progressively optimize the effectiveness of Event Detection (ED) and tracking algorithms. In this regard, this paper presents an in-depth comprehensive review of the concept and methods involved in ED and tracking in social networks. We introduce mainstream event tracking methods, which involve three primary technical steps: ED, event propagation, and event evolution. Finally, we introduce benchmark datasets and evaluation metrics for ED and tracking, which allow comparative analysis on the performance of mainstream methods. Finally, we present a comprehensive analysis of the main research findings and existing limitations in this field, as well as future research prospects and challenges
Expansion, Fracturing, and Depoliticisation: UK Government Anti-trafficking Funding from 2011 to 2023
Get PDFAnti-trafficking policy discourses and funding trajectories in the UK are developing and expanding in a fractured way. This paper demonstrates that current policies and funding allocations primarily focus on supporting specific ‘victims’ and targeting indistinct ‘criminals’, rather than addressing the broader structural issues underlying human trafficking. This focus perpetuates ignorance of harm done at other scales. For example, supporting migrants who meet a narrow definition of ‘victims’ effaces how government-funded abuses of migrants exacerbate vulnerability to exploitation. Antitrafficking funding from the UK’s Official Development Assistance addresses both the individual and structural scales; however, structural problems are often framed as external, neglecting the impacts of UK policies that increase the vulnerability of migrants and lowpaid or casualised workers. We also demonstrate that the UK government’s anti-trafficking discourse and funding are increasingly fractured along spatial lines: with a (limited) emphasis on the rights of exploited individuals outside the UK coinciding with attacks on the rights of migrants inside. Instead of narrow, depoliticised anti-trafficking discourses, it is vital to critique government policies that cause structural harm and amplify migrants’ vulnerability to exploitation. This could involve defunding certain government activities that increase vulnerabilities rather than merely expanding individual-level funding
“It’s been a hard year”: How families who have children with disabilities and chronic health conditions experience the COVID-19 pandemic
Get PDFBackgroundFamilies of children with disabilities and chronic health conditions experience unique challenges associated with school, therapies, and social supports. However, little is known about the COVID-19 pandemic’s influence on these families.AimsTo understand the lived experiences of families with children with disabilities and chronic health conditions during the COVID-19 pandemic.Methods and ProceduresWe gathered narrative accounts from 25 mothers of children with disabilities and chronic health conditions using individual interviews (n = 19) and one focus group (n = 6). A phenomenological approach was used to analyze the data.Outcomes and ResultsThree overarching themes were identified: isolation, connection, and thriving. Families experienced isolation due to the pandemic causing stress and poor mental health; maintained social connections with other family members, friends, and care providers using virtual platforms; and discovered unexpected benefits from the pandemic including a better understanding of their children and a slower pace of life.Conclusions and ImplicationsTherapy and support for children with disabilities and their families should prioritize reducing everyday stress, developing social connections that leverage existing networks and identify potential new ones, implementing approaches that build on children’s strengths, and maintaining choice in delivery of professional and peer-led support
Reinforcement Q-Learning for PDF Tracking Control of Stochastic Systems with Unknown Dynamics
Get PDFTracking control of the output probability density function presents significant challenges, particularly when dealing with unknown system models and multiplicative noise disturbances. To address these challenges, this paper introduces a novel tracking control algorithm based on reinforce-ment Q-learning. Initially, a B-spline model is employed to represent the original system, thereby transforming the control problem into a state weight tracking issue within the B-spline stochastic system model. Moreover, to tackle the challenge of unknown stochastic system dynamics and the presence of multiplicative noise, a model-free reinforcement Q-learning algorithm is employed to solve the control problem. Finally, the proposed algorithm’s effectiveness is validated through comprehensive simulation examples
Antimicrobial treatment of neonatal meningitis
Get PDFPart two containing answers: https://doi.org/10.12968/jprp.2024.6.1.4
Graph learning with label attention and hyperbolic embedding for temporal event prediction in healthcare
Get PDFThe digitization of healthcare systems has led to the proliferation of electronic health records (EHRs), serving as comprehensive repositories of patient information. However, the vast volume and complexity of EHR data present challenges in extracting meaningful insights. This paper addresses the need for automated analysis of EHRs by proposing a novel graph learning model with label attention (GLLA) for temporal event prediction. GLLA utilizes graph neural networks to capture intricate relationships between medical codes and patients, incorporating hierarchical structures and shared risk factors. Furthermore, it introduces the Label Attention and Attention-based Transformer (LAAT) algorithm to analyze unstructured clinical notes as a multi-label classification problem. Evaluation on the widely-used MIMIC III dataset demonstrates the efficacy of GLLA in enhancing diagnostic prediction performance. The contributions of this research include a comprehensive analysis of existing models, the identification of limitations, and the development of innovative approaches to improve the accuracy and effectiveness of EHR analysis. Ultimately, GLLA aims to advance healthcare decision-making, disease management strategies, and patient outcomes
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