Yuan Liao, Federico Delussu, Sílvia de Sojo
et al.
Urban deprivation is traditionally measured using static, residence-based indicators, capturing the socioeconomic, demographic, and spatial conditions of neighborhoods. However, this approach overlooks how daily movement allows residents to navigate the city, potentially exposing them to opportunities that differ significantly from their residential environments. To bridge this gap, we quantify the extent of bubble breaking - travel to less deprived areas - by analyzing mobile phone mobility networks combined with satellite-derived deprivation indices across 64 cities in India and Mexico. We find that residents of deprived areas systematically travel to better-off locations to meet daily needs, exhibiting a compensatory mobility pattern that significantly exceeds expectations derived from gravity models based on population and road networks. This residual bubble breaking (the part gravity models can not explain) is associated with a tension in the built environment: while high local amenity diversity allows residents to satisfy needs locally, high amenity density and positive spillovers from neighboring areas is associated with movement across socioeconomic boundaries. Overall, residual bubble breaking reflects the extent to which residents rely on cross-neighborhood mobility to overcome local amenity deficits, a dimension of spatial inequality that residence-based measures leave unobserved.
The `15-minute city' has emerged as a central paradigm in urban planning, promoting universal access to work and essential services within short travel times. Its feasibility-particularly for commuting to work-has however rarely been examined quantitatively. Here, we show that proximity to employment is fundamentally constrained by the internal structure of urban economies. Combining urban geometry with empirically observed firm-size distributions, we derive a lower bound on commuting times that holds independently of planning choices or transport technologies. This bound reveals a sharp transition: when employment is sufficiently concentrated, no spatial rearrangement of workplaces can ensure uniformly short commutes, even under optimal placement. Applied to Paris and its near suburbs, we find that achieving universal 15-minute commutes would require substantial economic restructuring or differentiated mobility strategies. The relevant question is therefore not whether an $x$-minute city is achievable, but what the minimal feasible $x$ is given a city's economic structure and spatial scale.
Abstract Despite the Chinese government’s implementation of numerous policies aimed at promoting urbanization, the actual urbanization rate has not met expectations. Even when some rural migrants are presented with opportunities to convert to urban-hukou status, an increasing number of families opt to maintain a dual-hukou arrangement (where one spouse holds rural-hukou and the other holds urban-hukou). This phenomenon has garnered significant attention; however, the impact of diverse access to urban welfare on migrants’ hukou selection has been underexplored in existing research on hukou conversion. Access to urban welfare emerges as a critical factor influencing hukou selection decisions. This study constructs an analytical framework to examine the hukou arrangements of dual-hukou families, exploring the effects of various factors related to urban welfare acquisition on the hukou selection of rural migrants. Empirical results indicate that within dual-hukou families, migrants with rural-hukou status can obtain urban welfare through family support or market purchases. Consequently, to maximize family benefits, they prefer to retain their rural-hukou status rather than convert to urban-hukou. Conversely, possession of a qualification certificate from the host city negatively impacts rural-hukou retention. Additionally, rural migrants in dual-hukou families tend to favor cities with high-value hukou and express a desire to convert to local hukou status. These findings offer robust insights for policymaking, demonstrating resilience against sample self-selection bias and reverse causality.
Understanding the alignment of Eastern European immigrants’ attitudes with those of their host societies in Western Europe is critical for exploring cultural convergence and divergence, particularly in the context of mass migration and freedom of movement within the European Union (EU). This study examines the extent to which Polish migrants’ attitudes towards non-marital family forms − cohabitation, divorce, and single motherhood − align with those of both their host (Dutch) and sending (Polish) societies, thereby increasing understanding of the challenges involved in cultural assimilation processes in Europe. Using data from the Polish and Netherlands Generations and Gender Survey (GGS) and the Families of Poles in the Netherlands (FPN) survey, we estimate a series of regression models to assess how nativity status influences attitudes towards non-marital family forms. We further examine the role of social integration indicators − such as Dutch language proficiency and usage, post-migration education, and having a Dutch partner − in shaping these attitudes among Polish migrants.
Polish migrants show greater acceptance of cohabitation and divorce than Polish non-migrants, although their attitudes regarding divorce are more aligned with those of Dutch non-migrants than Polish non-migrants. They exhibit less acceptance of single motherhood than both Polish and Dutch non-migrants, and these attitudes are not significantly influenced by social integration factors typically associated with host-country assimilation. Our findings suggest that Polish migrants’ attitudes towards non-marital family forms reflect a mix of assimilation and sui generis adaptation, combining elements of origin and host cultures with views shaped by the unique conditions of migration. This study advances the literature on migrant acculturation by identifying unique patterns of attitudes among Polish migrants in the Netherlands. It also suggests that migrants are at the forefront of cultural encounters, contributing to greater convergence on some, but not all, attitudes across EU member states.
Urban groups. The city. Urban sociology, City population. Including children in cities, immigration
Víctor Pérez-Segura, Raquel Caro-Carretero, Antonio Rua
Abstract Climate migration has emerged as one of the fastest-growing lines of inquiry within migration studies. However, it suffers from a fundamental empirical–conceptual limitation: the absence of a definition that clearly distinguishes a climate migrant from a labour migrant. This research aims to determine how the specialised literature positions the phenomenon, which forms of mobility it recognises and the extent to which the geographical context of scientific production influences its territorial delineation. To this end, the territorial location of migrant populations was analysed in a sample of 1,059 articles drawn from the WoS, Scopus and LENS databases. The results indicate that 39% of the studies treat the phenomenon in a decontextualised manner — without linking it to specific populations or migration processes. When territories are mentioned, 27% of the references pertain to Bangladesh and the Pacific islands. It is also observed that territorial identification is conditioned by the country of production, which tends to situate the phenomenon in spaces with which it has pre-existing migratory, geographical or historical ties. These findings are discussed from the perspectives of Science and Technology Studies (STS), the Geography of Science and decolonial thought. It is concluded that research on climate migration reproduces the epistemological positions of the Global North — the main generator of knowledge in this field. This produces a symbolic territorialisation of the phenomenon guided by securitising frameworks and a tendency to prioritise climate as the decisive factor.
Ahmet Tayfur Akcan, İdris Yagmur, Murat Ergül
et al.
Abstract One of the most important reasons for international migration is unemployment, along with economic concerns. Domestic and international migration movements generally take place from regions with high unemployment to the regions where unemployment is low. Therefore, analyzing the labor market is important for predicting and directing migration movements. The World Bank grouping of countries includes 47 country groups according to their geographical and income status. In our study, the unemployment hysteresis of 48 groups, which includes the average of these 47 country groups and the world in general, has been analyzed. For the analysis of the unemployment hysteresis, six different variables were used: total unemployment rate, female unemployment rate, male unemployment rate, youth unemployment rate, youth female unemployment rate, and youth male unemployment rate. For analysis of unemployment hysteresis, the Fourier PANIC panel unit root test, which entered the literature in 2023, was used. Significant results were obtained for country groups. The results of the analysis show that the unemployment hysteresis is valid for total unemployment worldwide, while the natural rate hypothesis is prominent for youth and young males. While hysteresis is observed in total and male unemployment in low- and middle-income countries, the natural rate hypothesis is generally valid in high-income countries; however, hysteresis persists in female unemployment. Therefore, at the global level, encouraging controlled and need-driven migration movements from regions where the unemployment hysteresis is valid to regions where the natural rate hypothesis is valid, can contribute to reducing imbalances in labor markets. At the national level, selective labor transfer policies, taking into account labor market needs, can be implemented from regions with high unemployment hysteresis.
Eleonora Andreotti, Ulysse Marquis, Maurizio napolitano
et al.
Urban systems often exhibit scale-invariant properties, with power-law distributions observed in various spatial and temporal patterns of human behavior. A prominent example is the distribution of commercial activities and other Points of Interest (POIs) across cities. However, the mechanisms by which such heavy-tailed behaviors emerge from local urban dynamics remain poorly understood. In this work, we demonstrate that global inhomogeneity in the spatial distribution of POIs can arise from the aggregation of locally homogeneous processes. Using Foursquare data from the city of Bologna, we show that POI distributions exhibit clear power-law scaling when analyzed at city scale. We develop a theoretical framework in which this behavior naturally emerges from spatial clusters defined by shared intensity levels across disjoint areas, rather than spatial contiguity. By analytically and empirically linking these local processes to the observed global distribution, we provide a generative explanation for the emergence of scale-free patterns in urban commercial structure. To further relax the assumptions underlying the purely spatial model, and to account for the empirical observation that areas with similar activity intensity can be spatially disjoint, we introduce a hybrid hierarchical approach that combines spatial clustering with statistical heterogeneity across regions of comparable density, modeled via Poisson mixtures. This enables us to capture real-world deviations from local regularity while preserving interpretability. Our findings highlight a key insight: complex global phenomena in cities can arise from the spatial superposition of simple, locally uniform dynamics. This connection between micro-level homogeneity and macro-scale complexity offers new tools for interpreting, modeling, and classifying urban space.
Luís M. A. Bettencourt, Ivanna Rodriguez, Jordan T. Kemp
et al.
Cities are characterized by the coexistence of general aggregate patterns, along with many local variations. This poses challenges for analyses of urban phenomena, which tend to be either too aggregated or too local, depending on the disciplinary approach. Here, we use methods from statistical learning theory to develop a general methodology for quantifying how much information is encoded in the spatial structure of cities at different scales. We illustrate the approach via the multiscale analysis of income distributions in over 900 US metropolitan areas. By treating the formation of diverse neighborhood structures as a process of spatial selection, we quantify the complexity of explanation needed to account for personal income heterogeneity observed across all US urban areas and each of their neighborhoods. We find that spatial selection is strongly dependent on income levels with richer and poorer households appearing spatially more segregated than middle-income groups. We also find that different neighborhoods present different degrees of income specificity and inequality, motivating analysis and theory beyond averages. Our findings emphasize the importance of multiscalar statistical methods that both coarse-grain and fine-grain data to bridge local to global theories of cities and other complex systems.
Software visualization tools can facilitate program comprehension by providing visual metaphors, or abstractions that reduce the amount of textual data that needs to be processed mentally. One way they do this is by enabling developers to build an internal representation of the visualized software and its architecture. However, as the amount of displayed data in the visualization increases, the visualization itself can become more difficult to comprehend. The ability to display small and large amounts of data in visualizations is called visual scalability. In this paper, we present two approaches to address the challenge of visual scalability in 3D software cities. First, we present an approach to semantic zoom, in which the graphical representation of the software landscape changes based on the virtual camera's distance from visual objects. Second, we augment the visualization with a miniature two-dimensional top-view projection called mini-map. We demonstrate our approach using an open-source implementation in our software visualization tool ExplorViz. ExplorViz is web-based and uses the 3D city metaphor, focusing on live trace visualization. We evaluated our approaches in two separate user studies. The results indicate that semantic zoom and the mini-map are both useful additions. User feedback indicates that semantic zoom and mini-maps are especially useful for large software landscapes and collaborative software exploration. The studies indicate a good usability of our implemented approaches. However, some shortcomings in our implementations have also been discovered, to be addressed in future work. Video URL: https://youtu.be/LYtUeWvizjU
We estimate the number of street vendors in New York City. First, we summarize the process by which vendors receive licenses and permits to operate legally in New York City. We then describe a survey that was administered by the Street Vendor Project while distributing coronavirus relief aid to vendors operating in New York City both with and without a license or permit. Finally, we review ratio estimation and develop a theoretical justification based on the theory of point processes. We find approximately 23,000 street vendors operate in New York City: 20,500 mobile food vendors and 2,400 general merchandise vendors. One third are located in just six ZIP Codes: 11368 (16%), 11372 (3%), and 11354 (3%) in North and West Queens and 10036 (5%), 10019 (4%), and 10001 (3%) in the Chelsea and Clinton neighborhoods of Manhattan. Our estimates suggest the American Community Survey misses the majority of New York City street vendors.
Driven by advancements in photovoltaic (PV) technology, solar energy has emerged as a promising renewable energy source, due to its ease of integration onto building rooftops, facades, and windows. For the emerging cities, the lack of detailed street-level data presents a challenge for effectively assessing the potential of building-integrated photovoltaic (BIPV). To address this, this study introduces SolarSAM, a novel BIPV evaluation method that leverages remote sensing imagery and deep learning techniques, and an emerging city in northern China is utilized to validate the model performance. During the process, SolarSAM segmented various building rooftops using text prompt guided semantic segmentation. Separate PV models were then developed for Rooftop PV, Facade-integrated PV, and PV windows systems, using this segmented data and local climate information. The potential for BIPV installation, solar power generation, and city-wide power self-sufficiency were assessed, revealing that the annual BIPV power generation potential surpassed the city's total electricity consumption by a factor of 2.5. Economic and environmental analysis were also conducted, including levelized cost of electricity and carbon reduction calculations, comparing different BIPV systems across various building categories. These findings demonstrated the model's performance and reveled the potential of BIPV power generation in the future.
Cities generate gains from interaction, but citizens often experience segregation as they move around the urban environment. Using GPS location data, we identify four distinct patterns of experienced segregation across US cities. Most common are affluent or poor neighborhoods where visitors lack diversity and residents have limited exposure to diversity elsewhere. Less frequent are majority-minority areas where residents must travel for diverse encounters, and wealthy urban zones with diverse visitors but where locals sort into homogeneous amenities. By clustering areas with similar mobility signatures, we uncover rings around cities and internal pockets where intergroup interaction is limited. Using a decision tree, we show that demography and location interact to create these zones. Our findings, persistent across time and prevalent across US cities, highlight the importance of considering both who is mixing and where in urban environments. Understanding the mesoscopic patterns that define experienced segregation in America illuminates neighborhood advantage and disadvantage, enabling interventions to foster economic opportunity and urban dynamism.
This CEEMR special section examines encounters and interactions between migrants as newcomers and their hosts. Our exploration derives from harnessing, first, a sense of belonging and, second, social interactions as two interrelated processes of encounter. To the extent that the host develops a sense of belonging with the newcomers and cultivates social interaction with them as the others, the newcomers would become visible and encounters followed by meaningful interactions with them would be possible. To look at this from another perspective, the newcomers develop a sense of belonging with their hosts as they encounter them and engage in social interactions with them in their everyday. We note that there is ample research that takes a critical stance on integration and inclusion already but there is still space to explore encounters and interactions in greater detail and why they matter for newcomers and host societies to establish intimacies with each other.
Colonies and colonization. Emigration and immigration. International migration, City population. Including children in cities, immigration
Abstract Mobile academics have traditionally been conceived as cosmopolitan subjects who favor cultural diversity and search for new professional opportunities abroad. Their return to the homeland could therefore be interpreted as a sign of parochialism, which narrows down their professional opportunities and limits their exposure to global resources. In this article, we compare returning and non-returning academics with respect to their parochial and/or cosmopolitan tendencies. Drawing on a sample of 223 Israeli Early-Career Researchers (ECRs), we examine their cosmopolitan—or otherwise parochial—propensities and assess the effect they have on their return decisions. We use statistical tests to analyze the effects of cultural orientation, attachment to the homeland-based national community, and patriotic feelings on their propensity to return. Our findings suggest that in comparison with their co-nationals who opted to remain abroad, returning ECRs exhibit higher levels of parochialism, reflected through inter alia stronger communal dispositions and patriotic attachment as well as geographically limited job search.
Davide Bertelli, Marta Bivand Erdal, Anatolie Coşciug
et al.
Migrants’ property ownership in their countries of origin is often understood through the prism of return: both intended and actual return mobilities. Applying a transnational optic, this article unpacks the relationships between migrants’ property ownership ‘back home’ and their reflections on future moves and stays, not limited to possible return. We draw on 80 semi-structured interviews conducted in 2020 with Polish and Romanian migrants living in Barcelona and Oslo. They left their homeland, sometimes following domestic migration or international migration to other countries, before arriving in Spain and Norway. Based on these case studies of East–West migration within Europe, we contribute to work recognising the ongoing complex and diversified nature of mobilities in Europe. First, we detail what migrants’ property ownership looks like in practice – forms of ownership, types of property, location. Second, we focus on how owning property in Poland or Romania intersects with migrants’ considerations about moving or staying in the future, beyond return. Considerations about future (im)mobility shed light on transnational relationships, as these evolve over time and across space. Furthermore, we find that transnational property ownership in their countries of origin reveals much about migrants’ relations with people and places ‘back home’ and reflects the known non-linearity of migration stories. Overall, however, transnational property ownership is a poor predictor of both return plans and intentions.
Colonies and colonization. Emigration and immigration. International migration, City population. Including children in cities, immigration
Alexander Saff, Mayur Bhandary, Siddharth Srivastava
Bike sharing systems often suffer from poor capacity management as a result of variable demand. These bike sharing systems would benefit from models to predict demand in order to moderate the number of bikes stored at each station. In this paper, we attempt to apply a graph neural network model to predict bike demand in the New York City, Citi Bike dataset.