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New Evidence on Post-Brexit UK Migration Trends
Get PDFThis report was issued in June 2024 by Brunel University London. Centre for Law, Economics and Finance, available online at: https://www.brunel.ac.uk/research/Documents/centre-for-law-economics-and-finance/2024-Post-Brexit-Migration-Report.pdf . This report expands on the range of inquiries and issues addressed by the Manifesto di Londra
association over the past four years. Matteo and Federico extend their gratitude to the members of the association’s Migration Committee for their valuable insights and support.At foot of title page: Report – May 2024.The report co-authored by Dr Federico Filauri, Dr Matteo Pazzona and Dr Matilde Rosina provides new evidence on post-Brexit UK migration trends up to December 2023. The report analyses recent migration patterns, highlighting the complex interplay between policy changes, economic factors, and global events in shaping UK migration trends.:Key findings:
• In December 2023, net migration was 685,000, a 10% decrease from its all-time high in December 2022 (764,000), but still a 47% increase compared to December 2021 (466,000). Among internationals, 41% immigrated to the UK to work, 34% to study, 7% for family reasons, 11% for humanitarian and asylum, and 6% for other reasons.
• In December 2023, the Department for Work and Pensions recorded more than 1.11 million new NiNo registrations from internationals, comparable with 1.05 million in 2022, with non-EU nationals accounting for 91% of the total (led by India and Nigeria), and EU for the remaining 9% (led by Romania). Between 2022 and 2023 there has been a 46% rise in the granting of work visa, amounting to 616,371 in 2023.
• In 2023, the number of new international students marked a 3% decrease, for a total of 340,990. This is consistent with the 3% drop in study visa grants, which amounted to 605,504 in 2023. However, last year, almost a quarter (24%) of study visas have been granted to a dependant, a significant rise from the 4% in 2019.
• The number of small boat arrivals totalled 29,437, marking a 36% decrease compared to the previous year, and in line with 2021. The decline in 2023 is mainly driven by a vertical drop in the number of Albanian migrants, which decreased by 93%. Humanitarian visa grants amounted to 102,283 in 2023, almost half of which were on Ukraine schemes. However, the latter marked an 80% decrease compared to the previous year, which drove down the number of humanitarian visa grants by approximately two thirds.
• In 2023, there were 81,203 family-related visas granted in 2023, a 72% increase from
last year and an all-time high.The research for the current report was made possible by Brunel University’s Centre for Law, Economics, and Finance. The authors gratefully acknowledge the financial and technical support provided by CLEF
Economic Inequality, Life Expectancy, and Interpersonal Violence in London Neighborhoods
Get PDFData availability statement:
The data used in this study were derived from the following resources available in the public domain: London Datastore (https://data.london.gov.uk/) for Metropolitan Police data, and U.K. census-derived population and income data. Urban Big Data Centre (https://data.ubdc.ac.uk/) for London Ambulance Service data (which was previously hosted by the London Datastore). Derived variables that support the findings of this study are openly available in the Brunel University London Research Repository (Brunel Figshare) at https://doi.org/10.17633/rd.brunel.26030677Positive associations between levels of socioeconomic inequality and homicide rates have been reported at various geographical levels (e.g., between countries, states, cities, and neighborhoods within a city). However, the extent to which inequality predicts levels of non-lethal violence has been less frequently studied. The present study was conducted to investigate the association between socioeconomic inequality and levels of non-lethal interpersonal violence across neighborhoods of London during the period 2010 to 2012, using two independent data sources: Metropolitan Police service recorded violent crime and London Ambulance Service recorded assaults. Mean income per person and local life expectancy were included as additional predictors. Following exclusions due to census boundary changes, across 533 London wards, there were positive bivariate associations between both violence measures and a measure of inequality between neighborhoods (census lower layer super output areas [LSOAs]) within a ward. Moreover, there were negative bivariate associations between violence rates and both ward mean income and life expectancy measures for males and females. However, in a regression analysis only inequality and male life expectancy were consistent predictors of rates of interpersonal violence across outcome measures. The results of the present study provide further evidence of an association between levels of economic inequality and rates of interpersonal violence. The findings, for variation in rates of non-lethal violence across small geographical areas (neighborhoods), build on previous research that has mostly focused on rates of lethal violence and has tended to use aggregate measures across larger geographical areas.JM was supported by a Brunel University London, College of Health, Medicine & Life Sciences PhD Studentship
The role of economic news in predicting suicides
Get PDFJEL classification: I14; I15.Data availability: The authors do not have permission to share data.Appendix. Brief overview of the WordNet-Affect: A synset is a group of data elements that are considered semantically equivalent for the purposes of information retrieval. WordNet-Affect is an extension of WordNet Domains (see Magnini and Cavaglià, 2000), that includes a set of synsets suitable to represent affective concepts representing moods, situations eliciting emotions, or emotional responses. The authors specifically initially identified a set of words that directly refer to emotional states (e.g. fear, cheerful, sad). Then, they expanded this initial set by implementing an unsupervised algorithm that exploited a mechanism of semantic similarity to automatically acquire from a large corpus of texts (100 millions of words). The final data set includes 1641 terms characterising 28 different emotions. Further information on the approach are available at the web link https://wndomains.fbk.eu/wnaffect.html .In this paper we explore the role of media and language used to comment on economic news in nowcasting and forecasting suicides in England and Wales. This is an interesting question, given the large delay in the release of official statistics on suicides. We use a large data set of over 200,000 news articles published in six major UK newspapers from 2001 to 2015 and carry sentiment analysis of the language used to comment on economic news. We extract daily indicators measuring a set of negative emotions that are often associated with poor mental health and use them to explain and forecast national daily suicide figures. We find that highly negative comments on the economic situation in newspaper articles are predictors of higher suicide numbers, especially when using words conveying stronger emotions of fear and despair. Our results suggest that media language carrying very strong, negative feelings is an early signal of a deterioration in a population’s mental health
Does voluntarism work for the workplace inclusion of individuals with disabilities in a country with limited equality structures?
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The study explores measures designed explicitly to manage people with disabilities in a context where diversity interventions are incorporated voluntarily. Furthermore, it examines global organizations’ approaches to marginalized groups, such as people with disabilities, in a context where there is an explicit lack of state regulation on diversity measures.
Design/methodology/approach:
An abductive approach was adopted for the exploratory nature, which sought to understand how global organizations in a developing country utilize diversity management mechanisms to manage people with disabilities.
Findings:
The findings reveal that human resources departments of international organizations operating in a neoliberal environment demonstrate two distinct perspectives for individuals with disabilities: (i) inclusiveness due to legal pressures and (ii) social exclusion.
Originality/value:
We explored global organizations’ approaches to marginalized groups, such as people with disabilities, in the context of an explicit lack of state regulation on diversity measures and showed that the absence of coercive regulation leads to voluntary actions with adverse consequences. The paper expands theories that critique the inclusion of individuals with disabilities in untamed neoliberal contexts and explains how the responsibilization of institutional actors could enhance what is practical and possible for the workplace inclusion of individuals with disabilities. Without such institutional responsibilization, our findings reveal that disability inclusion is left to the limited prospects of the market rationales to the extent of bottom-line utility
Public Perceptions of Human Excretion-Based Fertiliser in England and Japan
Get PDFData availability: Survey data and replication code are available on the Harvard Dataverse, at https://doi.org/10.7910/DVN/0VNQPP.This study investigates public attitudes towards the use of human excretion-based fertiliser (HEBF) in agriculture. Focusing on England and Japan, countries with contrasting histories of nightsoil use, we conducted representative surveys to understand public acceptance and sex-based differences in attitudes. Our findings reveal significant cultural and sex-based disparities in the willingness to utilize HEBF. The Japanese are more accepting of using HEBF for food production, with fewer health concerns, compared to the English. However, English respondents are more open to using HEBF in public parks. The study emphasises the need for further research on societal perceptions and highlights the importance of cultural context in adopting sustainable practices like HEBF in agriculture.UKRI/ ESRC (grant number ES/W011913/1) and the JSPS (grant number JPJSJRP 20211704)
Circular supply chain management in post-pandemic context. A qualitative study to explore how knowledge, environmental initiatives and economic viability affect sustainability
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Circular supply chain management (CSCM) is considered a promising solution to attain sustainability in the current industrial system. Despite the exigency of this approach, its application in the food industry is a challenge because of the nature of the industry and CSCM being a novel approach. The purpose of this study is to develop an industry-based systematic analysis of CSCM by examining the challenges for its application, exploring the effects of recognised challenges on various food supply chain (FSC) stages and investigating the business processes as drivers.
Design/methodology/approach:
Stakeholder theory guided the need to consider stakeholders’ views in this research and key stakeholders directly from the food circular supply chain were identified and interviewed (n = 36) following qualitative methods.
Findings:
Overall, the study reveals that knowledge, perception towards environmental initiatives and economic viability are the major barriers to circular supply chain transition in the UK FSC.
Originality/value:
This research provides a holistic perspective analysing the loopholes in different stages of the supply chain and investigating the way a particular circular supply chain stage is affected by recognised challenges through stakeholder theory, which will be a contribution to designing management-level strategies. Reconceptualising this practice would be beneficial in bringing three-tier (economic, environmental and social) benefits and will be supportive to engage stakeholders in the sustainability agenda
Constant or inconstant? The time-varying effect of danmaku on user engagement in online video platforms
Get PDFPurpose: As an emerging video comment feature, danmaku is gaining more traction and increasing user interaction, thereby altering user engagement. However, existing research seldom explores how the effectiveness of danmaku on user engagement varies over time. To address this research gap, this study proposes a comprehensive framework drawing on social presence theory and information overload theory. The framework aims to explain how the effectiveness of danmaku in increasing user engagement changes over shorter time intervals. Design/methodology/approach: A research model was proposed and empirically tested using data collected from 1,019 movies via Bilibili.com, one of China's most popular danmaku video platforms. A time-varying effect model (TVEM) was used to examine the proposed research model. Findings: The study finds that the volume of danmaku and its valence exert a time-varying influence on user engagement. Notably, the study shows that danmaku volume plays a more substantial role in determining user engagement than danmaku valence. Originality/value: This research offers theoretical insights into the dynamic impact of danmaku on user engagement. The innovative conceptualization and measurement of user engagement advance research on pseudo-synchronous communication engagement. Furthermore, this study offers practical guidelines for effectively managing danmaku comments on online video platforms
Decoding The Networking Strategies of Asian and Black Workers in the London Insurance Market
Get PDFParts of this paper’s findings were presented at the Equality, Diversity and Inclusion Conference 2023 in London. I would like to extend my appreciation to Professor Mustafa Özbilgin, who chaired the session, and the conference delegates whose insights and questions influenced the direction of this research.Purpose:
This study utilizes Bourdieu’s concepts of field, capital and habitus to investigate the networking strategies of Asian and Black knowledge workers in the London Insurance Market. It also examines the factors contributing to the success or failure of these strategies. The trading activities of the London Insurance Market are underpinned by interdependent relations among its participants. It provides an appropriate context for examining the networking strategies adopted by Asian and Black workers to accelerate their careers.
Design/methodology/approach:
This research employed a qualitative methodology, gathering data from 24 participants through semi-structured interviews. Participants were selected using purposive, convenience, and snowball sampling methods. Thematic analysis was used to analyze data and develop aggregated concepts from the identified themes and subthemes.
Findings:
The London Insurance Market accords great importance to networking. Interpersonal connections significantly influenced career progression, often overshadowing educational attainments. Asian and Black workers faced systemic nepotism and limited access to influential networks in this field. Participants strategically used their interactions to overcome these challenges and advance their careers. Many believed that their careers had a better chance of progressing through informal networks than through formal channels such as Human Resources. Some participants declined to engage in the commonly accepted networking practices, choosing alternative ways to further their careers.
Practical implications:
Findings underscore the need for implementing specific organizational policies to address systemic biases and nepotism, particularly in front-office recruitment. Such policies could include prioritizing merit-based hiring practices and developing targeted initiatives to reduce the underrepresentation of minority ethnic workers in front-office positions. By adopting these measures, organizations can create more equitable career advancement opportunities and leverage the full potential of their diverse workforce.
Originality/value:
This study contributes to the existing literature on minority ethnic workers' careers, networking theory and workplace diversity. It provides insights into the networking strategies of Asian and Black workers within the London Insurance Market, revealing that these strategies are dependent on contextual factors. The study also highlights the pervasive practice of nepotism deeply ingrained in the habitus of the London Insurance Market and which acts as a barrier for gaining access to influential networks
Automated Left Ventricle Segmentation in Echocardiography Using YOLO: A Deep Learning Approach for Enhanced Cardiac Function Assessment
Get PDFData Availability Statement: The data presented in this study are available on request from the corresponding author.Accurate segmentation of the left ventricle (LV) using echocardiogram (Echo) images is essential for cardiovascular analysis. Conventional techniques are labor-intensive and exhibit inter-observer variability. Deep learning has emerged as a powerful tool for automated medical image segmentation, offering advantages in speed and potentially superior accuracy. This study explores the efficacy of employing a YOLO (You Only Look Once) segmentation model for automated LV segmentation in Echo images. YOLO, a cutting-edge object detection model, achieves exceptional speed–accuracy balance through its well-designed architecture. It utilizes efficient dilated convolutional layers and bottleneck blocks for feature extraction while incorporating innovations like path aggregation and spatial attention mechanisms. These attributes make YOLO a compelling candidate for adaptation to LV segmentation in Echo images. We posit that by fine-tuning a pre-trained YOLO-based model on a well-annotated Echo image dataset, we can leverage the model’s strengths in real-time processing and precise object localization to achieve robust LV segmentation. The proposed approach entails fine-tuning a pre-trained YOLO model on a rigorously labeled Echo image dataset. Model performance has been evaluated using established metrics such as mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 50% (mAP50) with 98.31% and across a range of IoU thresholds from 50% to 95% (mAP50:95) with 75.27%. Successful implementation of YOLO for LV segmentation has the potential to significantly expedite and standardize Echo image analysis. This advancement could translate to improved clinical decision-making and enhanced patient care.This research received no external funding
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