The barriers to social integration posed by ethnic residential segregation are currently receiving renewed attention in Great Britain. A common characteristic of past studies of ethnic segregation in Britain is reliance upon aggregated Census data, raising potential issues of ecological fallacy. In this study, we address this challenge by using novel individual-level Consumer Register data for the UK to calculate an entropy-based spatial segregation index. We measure changes in segregation over twenty years and examine the impact of geographic scales upon observed levels of segregation in five policy relevant case study areas. Our results and findings can be used to improve the evidence base on segregation dynamics in the United Kingdom and have methodological implications for the future study of the phenomenon.

Objective: Occupational stress is a critical global public health problem. We aimed to evaluate the prevalence of occupational stress among the workers in the electricity, heat, gas, water production and supply (EHGWPS), manufacturing, and transportation industries in Beijing, China. We explored the demographic differences in occupational stress status among workers in industrial enterprises.Methods: A cross-sectional study was conducted on 13,867 workers. The self-administered New Brief Job Stress Questionnaire was used to evaluate high occupational stress status, which includes four sub-dimensions (job stressors, stress response, social support, job stressors & social support). Multiple regression and logistic regression models were used to estimate the association between high occupational stress and the four occupational stress sub-dimensions with risk factors.Results: A total of 13,867 workers were included. The prevalence of high occupational stress was 3.3% in the EHGWPS industries, 10.3% in manufacturing, and 5.8% in transportation. The prevalence of high occupational stress was higher than in the other two categories (p < 0.05) in manufacturing industries. Logistic regression analysis showed that male workers with lower educational status, more job experience, and working in manufacturing were vulnerable to high occupational stress. Further analysis of the four occupational stress sub-dimensions showed that male workers, older adult workers, workers with lower educational levels, and longer working time were associated with higher scores in job stressors, stress response, social support, and job stress & social support (all p < 0.05). Moreover, divorced or widowed workers had higher occupational stress scores.Conclusion: Male workers with lower educational levels and longer working time may have an increased risk of occupational stress.

The rapid evolution of Artificial Intelligence (AI) has ushered in a transformative era for urban studies, moving beyond traditional analytical methods to advanced Deep Learning architectures, with Transformers model in the spotlight. Yet, unlike bioinformatics, which has successfully utilised AI to decode static biological systems, or cheminformatics, which optimises chemical synthesis, urban informatics grappled with human-centric complexity that encompass subjective perceptions, socio-political dynamics, and multifaceted challenges that defy deterministic solutions. To avoid techno-solutionist pitfalls, we convened an interdisciplinary group of scholars to explore AI-powered urban informatics and proposed a Human-AI Symbiosis framework to foster sustainable cities and advance urban research. This Opinion paper synthesises insights into four key research directions, focusing on the evolving landscape of urban informatics and its potential to drive innovation in sustainable cities, policy-making, and societal development.

Geocoding historical addresses is a primary yet nontrivial application of spatial analysis in historical geographic information systems (GIS) and spatial humanities. We demonstrate our endeavours of geo-referencing and visualising historical census addresses in England and Wales, by matching the residential addresses to a historical gazetteer and a contemporary address database of Britain. The results indicate that it is feasible to standardise and geocode a large share of unique addresses from the historical database. The historical gazetteer and the modern address registers are two complementary data assets that can be used to geo-reference both well-formatted addresses in urban areas and non-standard addresses such as place names or building names in rural areas. The geo-referenced historical census data open up new opportunities for a broad spectrum of geo-demographic research on historical population characteristics at the micro level in England and Wales.

Empirical analysis of social mobility is typically framed by outcomes recorded for only a single, recent generation, ignoring intergenerational preconditions and historical conferment of opportunity. We use the detailed geography of relative deprivation (hardship) to demonstrate that different family groups today experience different intergenerational outcomes and that there is a distinct Great Britain-wide geography to these inequalities. We trace the evolution of these inequalities back in time by coupling family group level data for the entire Victorian population with a present day population-wide consumer register. Further geographical linkage to neighbourhood deprivation data allows us to chart the different social mobility outcomes experienced by every one of the 13,378 long-established family groups. We identify clear and enduring regional divides in England and Scotland. In substantive terms, use of family names and new historical digital census resources are central to recognising that geography is pivotal to understanding intergenerational inequalities.