Introduction. Social and territorial inequality determines differences in the life prospects of Russian youth. Heterogeneous living conditions in large cities, small towns, and rural areas generate unequal starting opportunities, influencing the formation and implementation of life strategies. The aim of this study is to identify similarities and differences in the social characteristics of urban and rural youth, as reflected in their life dispositions and strategies.
Materials and Methods. This article analyzes data from a 2023 online survey conducted in the Belgorod Region among urban and rural youth (schoolchildren, students, and workers) aged 14 to 35 (n = 5,881). The sample was quota-based based on gender, age, settlement type, and area of residence. Participants were recruited using a hot recruitment technique. Data processing was performed using Vortex software, with the construction of linear and cross-tabulation tables (based on respondents' settlement types). The dependent variables were twelve life strategies (economic, political, career, matrimonial, social, migration, self-realization, etc.), operationalized through the categories of ‘‘life dispositions’’ and ‘‘life plans’’.
Results. Despite a general value consensus (homogeneity of life dispositions), the life plans of young people demonstrate a stable stratification. Young people in large cities (regional centers) outperform their peers in small towns and villages in terms of aspirations across all strategies studied: from financial practices and career ambitions to reproductive plans and readiness for complex forms of socio-political participation. The statistically significant convergence of life planning indicators among young people in small towns and rural communities suggests the formation of a single continuum of ‘‘peripherality’’. The main mechanisms blocking the realization of ambitions are a lack of resources and a subjectively lower assessment of the opportunities for achieving goals in their region.
Discussion and Conclusion. The settlement factor is a significant mechanism of stratification, reproducing inequality in the practical feasibility of life projects. The gap in the complexity and scale of planning between the center and the periphery creates the risk of further concentration of human capital in large cities and depopulation of smaller territories. The materials in this article may be of interest to state youth policy authorities at various levels, as well as to state and municipal administrations; youth organizations; and educational institutions.
Over the past 20 years, the extensive expansions of informal settlements in built-up districts of developing countries have emerged as a major topic of discussion in the field of urbanization. However, peri-urban land use conflicts have resulted from the regional government's lateness in improving informal settlements. Moreover, formal and informal actors in urban fringe land use conflicts have not been clearly identified by a number of authors, despite their exploration of the link between the two. The objective of this study is to identify formal and informal actors in peri-urban land use disputes and to present a comprehensive, cross-sectoral analysis of peri-urban land use conflicts. Key land use actors in the urban–rural outskirts of Mekelle City were participated in 37 semi-structured interviews, which were followed by 12 focus group discussions. Besides, stakeholders' analysis and snowball methods were also used to answer research questions. The findings showed that friends, family, neighbors, community organizations and their immediate networks are informal actors engaged in peri-urban land disputes. In addition, government institutions, officials and authorities that set laws and regulations were identified as formal actors.
Abstract Artificial Intelligence (AI) is entirely coincident with the emergence of the digital computer. It was assumed from the start, some 75 years ago, that the computer had more than the required power to simulate human intelligence. This led to the speculation that ultimately computers would take over many of our own tasks which we once considered could never be modelled using machines. Here, we sketch the history and evolution of AI, note the different phases in this history, define distinctions between strong and weak AI, and emphasise the difference between generative and discriminative processes. There are many possible applications in city planning with the most suggestive and possibly the most disruptive being those related to the development of new methods for generating sustainable plans and designs. We make a key distinction between inductive and deductive AI, demonstrating these differences with methods of machine learning (ML), showing how early network methods based on the perceptron, can be linked to deductive procedures that enable us to build new models for city design. Our key illustration links urban simulation models to land cover built around geospatial data infused with ML. The aim of this paper is to chart the progress in AI and its applicability to city science and city planning from its first applications and speculate on future developments.
Cities. Urban geography, Urban groups. The city. Urban sociology
Robert Klein, Elias Willberg, Silviya Korpilo
et al.
Cycling is a cornerstone of a sustainable mobility transition in cities. Cycling research depends on the data available, but it has been difficult to produce or access these data in comparable ways. Sports tracking platforms like Strava have been transformative in mass-tracking cycling patterns and data sharing through applications and data competitions. Nevertheless, access to data has remained limited. Here, we present a framework that draws on the openly accessible Strava Global Heatmap to estimate spatial patterns of relative cycling intensity on an urban scale. To refine the raw heatmap outputs, we weighted them with population and point of interest (POI) counts within varying buffers. The cycling patterns were validated in a global context, comparing the heatmap values with cycle count data from 29 cities. Both population and POI weighting delivered high correlations in most cases between the heatmap and the cycle counts, POI weighting performing better overall. The strongest associations between Strava heatmap and cycle counts were observed in European cities and along the North American east coast, with p>0.7 for all, and p>0.8 for most cities. Additionally, the performance of our approach improved with higher cycling modal share at the city level. We demonstrate that a POI-weighted Strava heatmap can accurately represent urban cycling patterns and provide estimates of categorical cycling volumes. Our approach can be applied with relatively low effort to support the planning for urban cycling if official counts are sparse. Furthermore, it can enable the use of consistent cycling data for large-scale urban cycling analyses.
In the mediaeval Church in England, half of the diocesan cathedrals were also monastic communities; this phenomenon was virtually unique in the Church worldwide. Even after the Reformation, the monastic character of cathedrals continued to have a profound influence on the liturgy of the Church of England and on cathedrals as places to maintain the daily worship of God in solemn and musical form; to be homes for libraries and scholarship, and to be places of retreat and contemplative prayer. Norwich Cathedral was the last of these monastic cathedrals to be established (1096) and the first of the monastic cathedrals to be dissolved (1538). Particularly since the mid-nineteenth century, it has self-consciously been recovering a Benedictine character to its mission and ministry, most recently in the reconstruction of three monastic buildings lost since the Reformation: the Library reading room, the Refectory, and the Hostry. These buildings, while modern in design, build upon the remaining monastic fabric and echo the proportions and materials of their monastic predecessors, exemplifying the monastic vows of stability, obedience, and conversion of life. The Cathedral’s Benedictine principles extend to its ethos as an employer and commercial enterprise.
Aesthetics of cities. City planning and beautifying, Urban groups. The city. Urban sociology
This study examines the dynamics of the urban heat island (UHI) effect by conducting a comparative analysis of air temperature hysteresis patterns in Paris and Madrid, two major European cities with distinct climatic and urban characteristics. Utilizing high-resolution modelled air temperature data aggregated at a fine temporal resolution of three-hour intervals from 2008 to 2017, we investigate how diurnal and seasonal hysteresis loops reveal both unique and universal aspects of UHI variability. Paris, located in a temperate oceanic climate, and Madrid, situated in a cold semi-arid zone, display pronounced differences in UHI intensity, seasonal distribution, and diurnal patterns. Despite these contrasts, both cities exhibit remarkably similar hysteresis loop directions and slopes, suggesting that time-dependent mechanisms such as solar radiation and heat storage fundamentally govern air temperature UHI across diverse urban contexts. Our findings underscore the importance of considering both local climate and universal physical processes in developing targeted, climate-resilient urban strategies. The results pave the way for group-based interventions and classification of cities by hysteresis patterns to inform urban planning and heat mitigation efforts.
Ovidio García-Oliva, Carsten Lemmen, Xiangyu Li
et al.
Episodes of low dissolved oxygen concentration--hypoxia--threaten the functioning of and the services provided by aquatic ecosystems, particularly those of urban rivers. Here, we disentangle oxygen-related processes in the highly modified Elbe River flowing through the major German city of Hamburg, where low oxygen levels are frequently observed. We use a process-based biochemical model that describes particulate and dissolved organic matter, micro-algae, their pathogens, and the key reactions that produce or consume oxygen: photosynthesis, re-aeration, respiration, mineralization, and nitrification. The model analysis reveals pronounced spatial variability in the relative importance of these processes. Photosynthesis and respiration are more prominent upstream of the city, while mineralization, nitrification, and re-aeration prevail downstream. The city, characterized by rapid changes in bathymetry, marks a transitional area: pathogen-related micro-algal lysis may increase organic material, explaining the shift towards heterotrophic processes downstream. As the primary driver of seasonal changes, the model analysis reveals a differential temperature sensitivity of biochemical rates. These results may be extrapolated to other urban rivers, and also provide valuable information for estuarine water quality management.
Uncrewed Aerial Vehicles (UAVs) serving as Aerial Base Stations (ABSs) are expected to extend 6G millimeter-Wave (mmWave) coverage and improve link reliability in urban areas. However, UAV-based Air-to-Ground (A2G) channels are highly dependent on height and urban geometry. This paper proposes an ABS height-dependent mmWave channel model and investigates whether urban geometry, beyond the standard built-up parameters, significantly affects LoS probability (PLoS) and Large-Scale Fading (LSF). Using MATLAB ray tracing at 26 GHz, we simulate approximately 10K city realizations for four urban layouts that share identical built-up parameters but differ in their spatial organization. We extract elevation-based PLoS using a sigmoid model and derive height-dependent Path-Loss Exponents (PLEs) and shadow-fading trends using exponential fits. Results show that PLE for Non-Line-of-Sight (NLoS) decreases toward 2.5-3 at high altitudes, Line-of-Sight (LoS) PLE remains near 2, and shadow fading reduces with height. We also find that geometric layout introduces a modest but consistent change in PLE (+/- 0.2), even when built-up parameters are fixed. The proposed unified model aligns well with ray-tracing statistics and offers a practical, height-dependent LSF model suitable for ABS planning in complex urban scenarios.
Grant Buster, Jordan Cox, Brandon N. Benton
et al.
As urbanization and climate change progress, urban heat becomes a priority for climate adaptation efforts. High temperatures concentrated in urban heat can drive increased risk of heat-related death and illness as well as increased energy demand for cooling. However, estimating the effects of urban heat is an ongoing field of research typically burdened by an imprecise description of the built environment, significant computational cost, and a lack of high-resolution estimates of the impacts of climate change. Here, we present open-source, computationally efficient machine learning methods that can improve the accuracy of urban temperature estimates when compared to historical reanalysis data. These models are applied to residential buildings in Los Angeles, and we compare the energy benefits of heat mitigation strategies to the impacts of climate change. We find that cooling demand is likely to increase substantially through midcentury, but engineered high-albedo surfaces could lessen this increase by more than 50%. The corresponding increase in heating demand complicates this narrative, but total annual energy use from combined heating and cooling with electric heat pumps in the Los Angeles urban climate is shown to benefit from the engineered cooling strategies under both current and future climates.
There are many benefits and costs that come from people and firms clustering together in space. Agglomeration economies, in particular, are the manifestation of centripetal forces that make larger cities disproportionately more wealthy than smaller cities, pulling together individuals and firms in close physical proximity. Measuring agglomeration economies, however, is not easy, and the identification of its causes is still debated. Such association of productivity with size can arise from interactions that are facilitated by cities ("positive externalities"), but also from more productive individuals moving in and sorting into large cities ("self-sorting"). Under certain circumstances, even pure randomness can generate increasing returns to scale. In this chapter, we discuss some of the empirical observations, models, measurement challenges, and open question associated with the phenomenon of agglomeration economies. Furthermore, we discuss the implications of urban complexity theory, and in particular urban scaling, for the literature in agglomeration economies.
This study examined how Social Cognitive Theory (SCT) constructs help explain the intention to quit e-cigarettes in young Australian adults aged 18–24 years to inform vaping cessation programs. A cross-sectional survey of young adult vapers (<i>n</i> = 422) between March and the end of May 2023 examined personal, environmental, and behavioural factors of vaping cessation. Hierarchical multiple regression analysis examined the effects of SCT constructs on intention to quit vaping, controlling for covariates. Results found, in our sample consisting of 68% (<i>n</i> = 360) females, 18% (<i>n</i> = 95) males and 14% (<i>n</i> = 77) others, almost two-thirds (59.7%) of participants reported a quit attempt in the last year; with quit attempts being associated with quit intention (<i>p</i> ≤ 0.001). Model 1 (past year quit attempt, gender, educational attainment) accounted for 28.7% of the variance in quit intentions, with the addition of Model 2 SCT constructs adding a further significant 6.3% variance. Self-efficacy (B = 0.164, <i>p</i> ≤ 0.001), benefits (B = −0.106, <i>p</i> = 0.041) and social norms (B = −0.086, <i>p</i> = 0.035) had significant independent associations with quit intention. Findings demonstrate the SCT theoretical framework is suitable for use when developing vaping cessation programs, identifying the SCT constructs as important factors for quit intention. The findings can be used to inform the development of evidence-based vaping cessation programs to encourage vapers to quit and/or better support them in the quitting process.
The paper critically reviews communicative and agonistic planning theories from the viewpoint of a systemic turn in deliberative democracy theory. While the approach reveals complementarities between the theories, it also argues that each theory is vulnerable to criticism because of an ‘institutional gap’. The theories are found to complement each other in addressing planning conflicts at different dimensions. Communicative planning theory deals with conflicts between different stakeholders’ interests in planning processes. Agonistic planning theory, in turn, concentrates on conflicts from a more ontological dimension, related to the (implicit) conflict between hegemonic and marginalized discourses and related identity-forming processes of inclusion and exclusion in planning policies and governance. The institutional gap of communicative planning theory is argued to reside in its focus on situational deliberation that largely ignores the institutional dimension of rules and norms of democratic conduct. Agonistic pluralism, in turn, does engage with the dimension of democratic institutions, but in an overly critical manner, making it difficult for agonistic planning theory to address the dynamic interplay between institutional reconfiguration and policy stabilization in planning. This is argued to be the institutional gap of agonistic planning theory. The paper calls for further work in the field of planning theory to incorporate a systemic approach to deliberative democracy and thereby tap into the dialectics of institutional and situational dimensions of planning.
Cities. Urban geography, Urbanization. City and country
Many existing 3D semantic segmentation methods, deep learning in computer vision notably, claimed to achieve desired results on urban point clouds. Thus, it is significant to assess these methods quantitatively in diversified real-world urban scenes, encompassing high-rise, low-rise, high-density, and low-density urban areas. However, existing public benchmark datasets primarily represent low-rise scenes from European cities and cannot assess the methods comprehensively. This paper presents a benchmark dataset of high-rise urban point clouds, namely High-Rise, High-Density urban scenes of Hong Kong (HRHD-HK). HRHD-HK arranged in 150 tiles contains 273 million colorful photogrammetric 3D points from diverse urban settings. The semantic labels of HRHD-HK include building, vegetation, road, waterbody, facility, terrain, and vehicle. To our best knowledge, HRHD-HK is the first photogrammetric dataset that focuses on HRHD urban areas. This paper also comprehensively evaluates eight popular semantic segmentation methods on the HRHD-HK dataset. Experimental results confirmed plenty of room for enhancing the current 3D semantic segmentation of point clouds, especially for city objects with small volumes. Our dataset is publicly available at https://doi.org/10.25442/hku.23701866.v2.
This study aims to innovatively explore adaptive applications of large language models (LLM) in urban renewal. It also aims to improve its performance and text generation quality for knowledge question-answering (QA) tasks. Based on the ChatGLM, we automatically generate QA datasets using urban renewal scientific literature corpora in a self-instruct manner and then conduct joint fine-tuning training on the model using the Prefix and LoRA fine-tuning methods to create an LLM for urban renewal. By guiding the LLM to automatically generate QA data based on prompt words and given text, it is possible to quickly obtain datasets in the urban renewal field and provide data support for the fine-tuning training of LLMs. The experimental results show that the joint fine-tuning training method proposed in this study can significantly improve the performance of LLM on the QA tasks. Compared with LoRA fine-tuning, the method improves the Bleu and Rouge metrics on the test by about 5%; compared with the model before fine-tuning, the method improves the Bleu and Rouge metrics by about 15%-20%. This study demonstrates the effectiveness and superiority of the joint fine-tuning method using Prefix and LoRA for ChatGLM in the urban renewal knowledge QA tasks. It provides a new approach for fine-tuning LLMs on urban renewal-related tasks.
Seyed Hadi Arabi, Mohammad Hasan Maleki, Hamed Ansari
This research seeks to identify and analyze the drivers affecting the future of the income sources of social security organization. The theoretical population was the managers of the social security organization and experts in this field. The sampling was done judgmentally, and the sample size amounts to 15 people. Data collection tools were interviews and questionnaires. As for the findings, 35 sub-drivers were classified as economic, socio-cultural, structural, financial and investment, policy, marketing, environmental and legal drivers. These drivers were screened by distributing expert questionnaires and using Binominal's test. 13 drivers have significance coefficient of less than five percent and were selected for final prioritization. These drivers were evaluated by the Copras method and account for three criteria of experts' expertise, certainty, and importance. The driver of using the capacity of FinTechs and their innovations for financing and investment had the highest priority. Accordingly, the concluding suggestions were: using digital financial technologies and artificial intelligence to increase investment efficiency, using new financing methods such as crowd-funding, avoiding divesting loss-making companies to the organization, and strengthening good and efficient governance in the holdings of the organization.
Cristina Bustos, Daniel Rhoads, Agata Lapedriza
et al.
Increased interaction between and among pedestrians and vehicles in the crowded urban environments of today gives rise to a negative side-effect: a growth in traffic accidents, with pedestrians being the most vulnerable elements. Recent work has shown that Convolutional Neural Networks are able to accurately predict accident rates exploiting Street View imagery along urban roads. The promising results point to the plausibility of aided design of safe urban landscapes, for both pedestrians and vehicles. In this paper, by considering historical accident data and Street View images, we detail how to automatically predict the impact (increase or decrease) of urban interventions on accident incidence. The results are positive, rendering an accuracies ranging from 60 to 80%. We additionally provide an interpretability analysis to unveil which specific categories of urban features impact accident rates positively or negatively. Considering the transportation network substrates (sidewalk and road networks) and their demand, we integrate these results to a complex network framework, to estimate the effective impact of urban change on the safety of pedestrians and vehicles. Results show that public authorities may leverage on machine learning tools to prioritize targeted interventions, since our analysis show that limited improvement is obtained with current tools. Further, our findings have a wider application range such as the design of safe urban routes for pedestrians or to the field of driver-assistance technologies.
In Men in Place: Trans Masculinity, Race, and Sexuality in America, sociologist Miriam J. Abelson offers a gripping contribution to conversations about masculinity, transgender experience, and the effects of place on identities. Abelson draws on 66 in-depth qualitative interviews in order to highlight the experiences of transgender men outside of the northern cities and coastal urban enclaves that provide the backdrop for most of the American sociological literature on LGBTQ life. The trans men in the sample were aged 19 to 55 years and lived in rural, suburban, and urban areas across the American West, Midwest, and Southeast. Three key contributions of Men in Place lie in its expansion of transfeminist scholarship; attention to our geographic imaginaries; and updating of our understanding of masculinities in the contemporary moment. The majority of scholarship focused on trans experience is not conducted by trans researchers, leading to methodological and analytical awkwardness in most cases and cissexist microaggression and rhetorical violence in others. A key strength of Men in Place is its treatment of trans people as subjects rather than objects of study. Men in Place avoids the cissexist pitfall of using transgender people as evidence of persistent gender socialization or as exemplars of the social construction of gender. As the final line of the introduction reads, ‘‘I take the perspective that trans men give us crucial insight about men as a group because, quite simply, they are men’’ (p. 24). Trans people are not often treated as taken-for-granted occupants of their gender identity, even within scholarship that uses their experiences to make larger points about gendered social processes. As a trans scholar who studies trans experience, I often find myself holding my breath while reading cis scholars’ accounts or interpretations of trans life. Abelson writes, ‘‘Due to the historical and continuing objectification of trans people in scholarship, I have often paused to reconsider whether I, as a non-trans-identified, gender nonconforming woman, should continue this project at all’’ (p. 24). I am thrilled that Abelson continued this project, as this work makes significant contributions to scholarship in transgender sociology, the sociology of space and place, and sociology of men and masculinities. Grounded in theories of doing gender, racial formation, and heteronormativity, one foundational assumption of Men in Place is that gender identity recognition is earned in social interaction through the achievement of situated normative ideals. With beautiful prose and vivid detail, the text takes us on a meticulous exploration of location as a determining factor for processes of identity, interaction, and inequality. The men in Abelson’s study rely on ‘‘geographic imaginaries’’ (p. 19) that provide them with information about their gendered, raced, and sexualized place within a particular community. These geographic imaginaries come with localized ideals for the normative practice of gender, race, and sexuality. What passes as masculinity, and who passes as a regular guy, in one region may not receive the same recognition in another. As Men in Place continuously reminds us, ideological constructs about queer and trans life beyond the coastal cities and urban enclaves of the United States operate to create a narrative of vulnerability for gender and sexual minorities in these areas. Abelson writes, ‘‘dominant discourses of rural queer and transgender life make rural trans men’s lives seem unlivable’’ (p. 198). Men in Place suggests that while this narrative acts as a powerful tool to encourage conformity to place-based norms and to discourage
This paper analyzes how in the Cold War, the prospective, linked to strategic planning, was an important key instrument in the design of the National Project of the Chilean dictatorship, as well as in the political and economic reorganization imposed by the regime. That methodology, advocated by civilian and military technocrats, served to provide a scientific framework to the re-founding project of the regime. In Latin America, prospective studies were linked to the principles of the National Security Doctrine, allowed to anticipate possible future scenarios, develop public policies and plan the urban development of the city of Santiago for 2000. In that sense, Herman Kahn, one of the leaders of the predictive method, was summoned by the Chilean military regime and guided Augusto Pinochet’s advisors on economic development to consolidate the bases of the “National Reconstruction.”
Cities. Urban geography, Urbanization. City and country