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Qualitative Interview Insights Report. Report prepared for the research funded by the Solicitors Regulation Authority on the potential causes of differential outcomes in legal professional assessments
Get PDFBraverman and Labor and Monopoly Capital:A Retrospective
Get PDFThis paper appraises the work of Harry Braverman (1920–76), specifically his classic, Labor and Monopoly Capital, published in 1974 and remaining an influential reference for what has become the labour process approach to the study of work in capitalist societies. Labor and Monopoly Capital (LMC) reshaped what was then known as industrial sociology in the English-speaking world and was impactful across a range of disciplines, including history, organisation and management studies, comparative political economy, and labour geography. It is widely regarded as the foundational text of labour process theory (LPT). Fifty years after the initial publication of LMC, that theoretical approach is not only alive and well, but in the past decade, undergone something of a resurgence, influencing global communities of scholars. The paper takes a close look primarily at the text in its context, examining the genesis of the arguments, the distinctive biography of the author, and the structure of the book drawing out its major and minor themes, including a critical assessment of sources and evidence. We argue that the enormous impact of LMC can be explained by its successful challenge to existing orthodoxies about trajectories in work, technology, and management dominant in the social sciences and orthodox Marxism. This is followed up with a discussion of the reception, diffusion, and development of LMC comparatively and across different geographic domains and academic disciplines. As the debate on LMC eventually became a much broader programme of theory and research on the labour process, we consider some of the key points of differentiation from one of the foundational texts. Whilst acknowledging its enduring legacy, the final section argues that there is only a route forward from, rather than back to Braverman, given the profound changes to global capital and labour in the 50 years since LMC appeared.<br/
How does migration impact on mental health and emotional wellbeing of migrants? A case study of 25 Filipino migrants in the United Kingdom
Get PDFThis thesis presents findings from a qualitative case study to explore the experiences and perceptions of 25 Filipino migrants in the United Kingdom (UK) on how migration has impacted their mental health and emotional well-being. Through semi-structured interviews and participant observation, this study determined the factors Filipino migrants associated with their mental health and emotional well-being, and what coping strategies they have used to deal with the impacts of migration. Although migration is a well-researched phenomenon, little is known about how Filipino migrants conceptualise mental health, nor is there a great deal of qualitative research on how their mental health is impacted by the experience of migration. The main thesis of this study was the significance of culture in the migrants’ understanding of mental health and in making sense of their migration experiences.Guided by Bhugra’s framework (2004), this study found sociological and economic factors that were associated with mental health including loss of social support, loss of identity, discrimination and racism, and financial obligation to the family. This study showed that for economic migrants, the voluntary nature of their migration and their motivation to migrate factored in coping with the impact of migration. Culturally appropriate coping strategies that correspond to Filipino values and norms include faith, religion, social support, or togetherness, and fulfilling the obligation of providing economic support to the family. This study offers another way of understanding the role of the family of the migrants and challenges some concepts of the migrant behaviour model where sending remittances is seen as an intertemporal contractual arrangement. Instead, the study highlights the deeply rooted sense of obligation by the migrants to fulfil their provider role.Finally, this study showed how qualitative research using a case study design could investigate a sensitive topic such as mental health and provide a voice to research participants. Using participant observation proved effective in understanding the dynamics of relationships within social groups and how culture manifests in social interactions.<br/
Essays on Asset Pricing: The role of liquidity in asset pricing within Stocks and Real Estate Investment Trusts
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Video deepfake detection using Particle Swarm Optimization improved deep neural networks
Get PDFAs complexity and capabilities of Artificial Intelligence technologies increase, so does its potential for misuse. Deepfake videos are an example. They are created with generative models which produce media that replicates the voices and faces of real people. Deepfake videos may be entertaining, but they may also put privacy and security at risk. A criminal may forge a video of a politician or another notable person in order to affect public opinions or deceive others. Approaches for detecting and protecting against these types of forgery must evolve as well as the methods of generation to ensure that proper information is supplied and to mitigate the risks associated with the fast evolution of deepfakes. This research exploits the effectiveness of deepfake detection algorithms with the application of a Particle Swarm Optimization (PSO) variant for hyperparameter selection. Since Convolutional Neural Networks excel in recognizing objects and patterns in visual data while Recurrent Neural Networks are proficient at handling sequential data, in this research, we propose a hybrid EfficientNet-Gated Recurrent Unit (GRU) network as well as EfficientNet-B0-based transfer learning for video forgery classification. A new PSO algorithm is proposed for hyperparameter search, which incorporates composite leaders and reinforcement learning-based search strategy allocation to mitigate premature convergence. To assess whether an image or a video is manipulated, both models are trained on datasets containing deepfake and genuine photographs and videos. The empirical results indicate that the proposed PSO-based EfficientNet-GRU and EfficientNet-B0 networks outperform the counterparts with manual and optimal learning configurations yielded by other search methods for several deepfake datasets
Mask R-CNN Transfer Learning Variants for Multi-Organ Medical Image Segmentation
Get PDFMedical abdomen image segmentation is a challenging task owing to discernible characteristics of the tumour against other organs. As an effective image segmenter, Mask R-CNN has been employed in many medical imaging applications, e.g. for segmenting nucleus from cytoplasm for leukaemia diagnosis and skin lesion segmentation. Motivated by such existing studies, this research takes advantage of the strengths of Mask R-CNN in leveraging on pre-trained CNN architectures such as ResNet and proposes three variants of Mask R-CNN for multi-organ medical image segmentation. Specifically, we propose three variants of the Mask R-CNN transfer learning model successively, each with a set of configurations modified from the one preceding. To be specific, the three variants are (1) the traditional transfer learning with customized loss functions with comparatively more weightage on the segmentation performance, (2) transfer learning based on Mask R-CNN with deepened re-trained layers instead of only the last two/three layers as in traditional transfer learning, and (3) the fine-tuning of Mask R-CNN with expansion of the Region of Interest pooling sizes. Evaluating using Beyond-the-Cranial-Vault (BTCV) abdominal dataset, a well-established benchmark for multi-organ medical image segmentation, the three proposed variants of Mask R-CNN obtain promising performances. In particular, the empirical results indicate the effectiveness of the proposed adapted loss functions, the deepened transfer learning process, as well as the expansion of the RoI pooling sizes. Such variations account for the great efficiency of the proposed transfer learning variant schemes for undertaking multi-organ image segmentation tasks
Rabbinic Literature and Roman-Byzantine Legal Compilations
Get PDFIt remains uncertain whether interest and influence or ignorance and indifference are the right words to describe the relationship between rabbinic literature and Roman-Byzantine legal compilations. The chapter surveys the mostly separate study of the Talmud Yerushalmi and Justinian’s Corpus Juris Civilis and discusses scholarly theories about their compositional history. It argues that comparative (machine-assisted) analysis may be more likely to reveal structural and conceptual similarities rather than direct impact or mutual dependence. It proposes to ask questions for which sufficient evidence exists and to refocus on the analysis of the texts
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