Impact of unemployment on skill depreciation: Evidence from China's labor market.

Optimal urban expansion rates for balancing ecosystem services and economic development in mega-city fringe areas: A modeling framework applied to Huadu district, Guangzhou

Intergenerational households and labor migration are common characteristics of many rural Chinese communities. Intergenerational caregivers offer various forms of autonomy support to nurture children's development, especially when parents migrate to industrialized areas for work. To understand such support, primary caregivers, including 21 parents and 24 grandparents from families with various migration trends, were recruited from a southwest rural village with a high migration flow. All caregivers participated in interviews about their developmental ideals for children and how they help children meet these expectations. All caregivers defined the developmental ideals as Zili (self-reliance), Qinkuai (diligence) when completing chores, Zijue (self-awareness) in learning, and social and reflective skills while putting self-directed effort into learning. Emphasis on educational attainment for future independence, expanding intellectual horizons, and imparting moral knowledge supported children's psychological autonomy. Welcoming children's personal preferences and granting children the necessary space to manage their time-ideals apparent in industrialized societies-were also evident. Action autonomy support included using chores to train action, expecting behavioral self-reliance, and forming relevant habits as early in the life cycle as practical. When comparing two generations, most grandparents emphasized children's effort in learning, whereas parents stressed children's prosocial behaviors, sibling roles, and commitment to expanding intellectual horizons. All caregivers from families experiencing long-term parental migration put more emphasis on children's academic self-awareness and effort, fulfilling children's preferences, and teaching moral judgment compared to short-term and nonmigrant families. Childrearing goals reflected adaptive responses to children's expression of autonomy and intergenerational support regardless of migration status. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Urban amenity and settlement intention of rural migrants in China: The mediating role of housing prices

Seasonal freeze-thaw modulates methane cycling in urban waters revealed by multiple isotopic constraints.

Urban flooding increasingly challenges rapidly expanding cities in developing countries. Migration, weak urban planning, and unregulated land use collectively intensify flood risk. Effective flood mitigation requires understanding the dynamic interactions between physical and social processes that shape urban vulnerability. This study examines how migrant households in flood-prone areas adapt over time to enhance resilience. The study applies a dynamic flood risk framework using settlement-duration cohorts from 560 peri-urban households in Phnom Penh. Findings show that rapid in-migration into flood-prone zones has increased physical exposure to flood hazards. Migrants’ adaptation and resilience, however, develop gradually, reducing vulnerability only over time. Newer migrants remain highly vulnerable due to insecure housing, limited renovation, and restricted access to flood information. Long-term migrants face structural and economic challenges, including low income, limited access to credit, and deteriorating housing conditions. Mid-term migrants demonstrate the strongest adaptive capacity, supported by stable income, housing investment, and access to flood information. Overall, the study contributes to more dynamic urban risk frameworks that incorporate demographic and socioeconomic transitions. These insights are relevant for other rapidly growing cities, particularly those in Southeast Asia.

With the rapid acceleration of global urbanization, urban community spatial planning faces increasingly complex multi-objective optimization challenges. Traditional planning methods, which rely heavily on expert experience, often struggle to adapt to the dynamic and nonlinear nature of urban environments, highlighting the urgent need for intelligent solutions. To address this, this study proposes a multi-agent, multi-scale optimization framework based on deep reinforcement learning. The framework decomposes urban spatial planning tasks into three levels—macro, meso, and micro—allowing for coordinated optimization across scales and achieving comprehensive spatial planning from overall layouts to local details. By integrating a grid-based foundational model with cellular automata, the framework provides agents with precise environmental inputs, enabling dynamic simulation of urban functional zone expansions. Experimental results demonstrate significant improvements in land-use efficiency, public service accessibility, and environmental harmony. Compared to traditional methods, the proposed approach exhibits superior flexibility and adaptability, offering robust technological support for the intelligent and automated evolution of urban spatial planning.

Introduction The exponential global urbanisation has demanded advanced governance frameworks capable of attaining complex socio-technological challenges through digitally enabled urban transformation. While first-generation smart city initiatives dealt primarily with technological implementation issues, Smart City 2.0 paradigms, in their more contemporary form, require a prerequisite and deep understanding of governance effectiveness, citizen engagement mechanisms, and cross-contextual implementation strategies. This work fills an essential gap in the state of knowledge on comparative Smart City governance by presenting a study on the nature of Smart City 2.0 implementation in India, Singapore, and Indonesia as Case Studies. Methods Employing a multidimensional comparative framework, this research aims to provide a structured and systematic analysis of governance structures, technology integration strategies, sustainability approaches, and citizen participation mechanisms across three urban development contexts. The methodology combines significant analysis of policy documents, data on implementation, and synthesis of theoretical frameworks to appraise the effectiveness of Smart City 2.0 across different political, economic, and social settings. The analytical framework examines four basic dimensions: models of governance and leadership; strategies for integrating technology; motivations around sustainability and a green environment; and ways citizens are engaged. Results Key findings include a fundamental need for contextual adaptation rather than universal standardisation in Smart City 2.0. India’s driven approach to scalability uses standardised frameworks with local adaptability, achieving a 94% completion rate across 8,067 projects in 100 cities. Singapore’s AI-backed Smart Nation 2.0 has demonstrated total inter-agency coordination, met 110% of the target dates for digital literacy rates, and provided strong infrastructure, ensuring cybersecurity. Collaborative governance model - Indonesia’s dependence on hegemonic digital infrastructure is evident in collaborative initiatives such as the JAKI super-app (6.4 million downloads) in Jakarta, which has been ‘glued’ together (grafted) with over 150 government applications. Discussion This comparative analysis restructures the paradigms of smart cities from a tech-centred emphasis towards a more realistic view of the fundamental contributing factors that are driving the success of Smart City 2.0, demonstrating that it is innovations in governance, capacity building of institutions and citizen-centred service delivery that are playing the central role in the effectiveness of Smart City 2.0. The results provide an evidence-based foundation for policy formulation to navigate the complexities of urban digital transformation and to support place-based governance strategies that integrate technological capacities within local governance structures, participatory mechanisms, and environmental sustainability objectives.

The disposal of contracted land by rural migrants in China is influenced by multidimensional and systemic factors, which result in the gradual formation of a distorted human–land relationship that is characterized as “leaving farming without leaving rights” and “abandoning cultivation without abandoning land.” This relationship severely restricts the efficiency of rural land use and the structural upgrading of agricultural industries. Using data from the China Migrants Dynamic Survey and applying a multinomial logit model, this study reveals the following findings: (1) individual characteristics, integration status, and migration factors collectively influence land disposal patterns, and they have distinct differences in characteristics, types, and regional variations; (2) in terms of individual characteristics, those rural migrants who are female, in good health, have a high level of education, own homestead land, have a large number of family members, contract a small land area, or face difficulties in dealing with the outflow of land tend to entrust their family members with continued farming rather than engaging in land transfer or abandonment when faced with the choice of contracted land disposal methods, whereas older migrants are more inclined to transfer their contracted land; (3) with respect to integration status in the inflow area, rural migrants with higher levels of economic integration and better identity integration are more likely to choose land transfer or abandonment over continued family cultivation. Conversely, those with greater levels of institutional integration are more likely to opt for continued family cultivation; (4) in terms of mobility factors, rural migrants from western regions and those with shorter migration distances are more likely to continue with family farming or abandon their contracted land. The longer the migration duration, the greater the likelihood of land abandonment. Groups that migrate for family reasons are more inclined toward land transfer or abandonment. The study concludes that the disposal of contracted land by rural migrants serves as a risk-hedging strategy and safety net against urban livelihood vulnerabilities. Multiple measures are needed to optimize disposal decisions and achieve efficient utilization of rural land resources.

ABSTRACT The current literature on the relationship between different globalisation indicators and the human development index (HDI) is contradictory and no specific relationship can be found between them. The aim of this study is to determine the necessary and sufficient conditions for different dimensions of globalisation at the level of HDI for 170 countries during 2005-2021. The results of the Necessary Condition Analysis (NCA) show that in the high-income countries, different dimensions of globalisation and urbanisation rates are essential for HDI, and in the low-income countries, the overall index of globalisation, political and social indexes, and urbanisation rates are essential for HDI. In addition, the Fuzzy Qualitative Comparative Analysis (fsQCA) has emphasised for both groups of countries that the dimensions of globalisation should be improved with high consistency to increase HDI. The findings indicate that policymakers should focus on increasing their interactions with the world to increase HDI.

China's urban-rural Integrated Medical Insurance System (IMIS) has expanded universal health coverage, reducing disparities in healthcare access between urban and rural populations and addressing challenges such as unequal access to medical care and reimbursement barriers for disadvantaged groups. Previous research highlights that health insurance influences medical risk, labor mobility, and income distribution, with women valuing and utilizing health insurance more than men. This study investigates IMIS's impact on women's entrepreneurship in China using data from the China Family Panel Studies (CFPS) and the China Statistical Yearbook. A Difference-in-Differences (DID) analysis reveals that IMIS increases the likelihood of women's entrepreneurship by 9.6 percentage points, with robustness confirmed through multiple tests. The study identifies reduced medical expenditure risk, increased access to high-risk occupations, and enhanced household bargaining power as key mechanisms driving this effect. Heterogeneity analyses show that younger women, those with higher education, rural-urban migrants, women with children, those in poorer health, and those with lower household income get greater benefits, underscoring IMIS's inclusivity. These findings demonstrate that IMIS promotes women's entrepreneurship, enhancing economic performance and welfare.

Introduction The essence of rural revitalization lies in achieving “affluent living” with common prosperity in rural areas being the focal point and challenge. As a key element of rural revitalization, industrial revitalization of rural areas plays a pivotal role in advancing common prosperity in rural communities. Methods This study is based on the panel data of 30 provinces in China from 2013 to 2023 (excluding Hong Kong, Macau, Taiwan, and Tibet), and has constructed an indicator system for rural industrial revitalization and common prosperity. Based on this, the fixed effect model and the mediation effect model were adopted to systematically evaluate the impact of rural industrial revitalization on rural common prosperity. Through various robustness tests such as endogeneity handling, machine learning verification, and placebo test, the reliability of the research results has been ensured. Results The research results indicate that rural industrial revitalization can significantly enhance the level of rural common prosperity, and this has been fully verified through various robustness tests. Furthermore, this effect shows significant heterogeneity. The effects are stronger in the central and western regions, as well as in the areas with low urbanization rates, compared to those in the eastern regions and areas with high urbanization rates. Finally, promoting income growth and improving human capital are crucial micro mechanisms for rural industrial revitalization and the promotion of common prosperity in rural areas of our country. Discussion Science-driven rural industrial revitalization and further clarification of the realization path for enabling rural common prosperity are of great significance for achieving the goal of common prosperity. This evidence highlights the necessity of formulating region-specific strategies, especially in underdeveloped and low-urbanization areas. Rural industrial revitalization can bring the greatest marginal benefits. The research conclusions of this article provide new ideas and inspiration for effectively promoting rural industrial development and achieving common prosperity in rural areas.

ABSTRACT Class remains curiously absent in rural migration scholarship of the Global North. Earlier studies highlighted the role played by class origin in capital accumulation and social mobility among migrants building futures in new country contexts. Yet class has been largely obscured or avoided in empirically-driven analyses of rural migration and rural multiculture over the past twenty-five years. This paper examines this omission through the lens of contemporary Australia, a burgeoning site of research on rural migrant settlement and mobilities. Australia’s rural towns and cities were historically engineered on classed colonial and racialised hierarchies. These conditions continue to structure rural social and economic life in the present – from schooling and employment relations, to social networks and resourcing. Drawing on extensive empirical research, this paper draws out the significance of class for the migration experiences of young people and their families from migrant backgrounds in the inland, rural city of Mildura in south-eastern Australia. Class is shown here to structure and shape rural migration in complex ways, both enabling and hindering anticipated and desired social mobilities and playing a key role in young people’s rural migration trajectories.

Grounded in the theory of active aging and considering the dual attributes of mobility and aging, this study systematically assessed the levels of active aging among older urban migrants and uncovered patterns of subgroup heterogeneity within this population. A cross-sectional comparative research design with quantitative methods was employed. Data were collected through a field survey conducted across four cities and 14 urban districts in within Zhejiang Province. A multidimensional evaluation framework was developed, encompassing six dimensions, including individual factors, health-related behaviors, economic conditions, social environments, physical environments, and health and social services. The findings revealed that the overall level of active aging among older urban migrants remained relatively low, with significant deficiencies across core dimensions such as volunteering participation, property ownership, healthcare utilization, and medical insurance accessibility. Moreover, substantial internal heterogeneity was observed, shaped by variations in migration motivation, geographical scale, and length of residence. Quality-of-life-oriented migrants demonstrated higher levels of active aging compared with family-support and economically-driven migrants, while inter-provincial migrants and short-term residents faced greater barriers to accessing health services, social participation, and urban integration. These findings underscore the need to shift public service delivery from a household registration-based model to a residency-oriented approach. Targeted interventions are needed to enhance social inclusion, institutional adaptation, and individual empowerment among older urban migrants. Furthermore, stronger policy coordination and localized support mechanisms are essential for optimizing active aging within urban contexts shaped by migration.

Adolescent girls affected by displacement face substantial mental-health risks. The Sibling Support for Adolescent Girls in Emergencies (SSAGE) is a 12-week, gender-transformative, family-based program designed to improve adolescent girls’ mental health in humanitarian settings. This mixed-methods pilot randomized controlled trial (RCT) assessed SSAGE’s feasibility, acceptability and potential effects among 186 Venezuelan migrant and Colombian returnee families in Colombia. Adolescent girls aged 13–19 years, their male siblings and caregivers participated in parallel sessions on gender dynamics, communication and relationships. Implementation outcomes drew on the Mental Health Implementation Science Tools (acceptability and feasibility subscales), attendance records and qualitative interviews. Analyses followed an intent-to-treat approach using adjusted linear and logistic regression models. Quantitative analyses did not identify measurable changes in adolescent girls’ mental health outcomes at endline; however, attendance was modest, with only ~10% of families meeting the predefined protocol threshold. Implementation findings revealed strong participant satisfaction and high acceptability of SSAGE content and mentor relationships. Engagement was constrained by economic hardship, transportation and venue barriers, and some caregivers’ acute emotional distress, which likely limited feasibility and potential impact. SSAGE shows promise as a gender-transformative, family-based approach, but successful delivery in urban migrant settings will require tailored and refined implementation strategies.

Adolescent girls affected by displacement face substantial mental-health risks. The Sibling Support for Adolescent Girls in Emergencies (SSAGE) is a 12-week, gender-transformative, family-based program designed to improve adolescent girls' mental health in humanitarian settings. This mixed-methods pilot randomized controlled trial (RCT) assessed SSAGE's feasibility, acceptability and potential effects among 186 Venezuelan migrant and Colombian returnee families in Colombia. Adolescent girls aged 13-19 years, their male siblings and caregivers participated in parallel sessions on gender dynamics, communication and relationships. Implementation outcomes drew on the Mental Health Implementation Science Tools (acceptability and feasibility subscales), attendance records and qualitative interviews. Analyses followed an intent-to-treat approach using adjusted linear and logistic regression models. Quantitative analyses did not identify measurable changes in adolescent girls' mental health outcomes at endline; however, attendance was modest, with only ~10% of families meeting the predefined protocol threshold. Implementation findings revealed strong participant satisfaction and high acceptability of SSAGE content and mentor relationships. Engagement was constrained by economic hardship, transportation and venue barriers, and some caregivers' acute emotional distress, which likely limited feasibility and potential impact. SSAGE shows promise as a gender-transformative, family-based approach, but successful delivery in urban migrant settings will require tailored and refined implementation strategies.

Global urbanization has promoted to an increasing scale of construction projects, thereby making the optimization of construction project organization design a critical task in engineering management. However, conventional methods relying on empirical decision-making suffer from issues like low resource allocation efficiency, many difficulties in coordinating multi-objective conflicts and insufficient dynamic adjustment capabilities. To address these issues, we propose the first multi-objective extension of the Animated Oat Optimization algorithm (MOAOO), which represents a pioneering contribution in transforming the single-objective AOO into a multi-objective optimizer for construction project organization design. The developed algorithm fundamentally extends the biological mechanism of Animated Oat Optimization introducing several key innovations: (a) a novel hybrid position update rule combining Elite Reference Points and stochastic perturbations to prevent premature convergence; (b) an innovative three-layer constraint processing mechanism ensuring the generation of feasible solutions; and (c) a dual-threshold convergence monitoring system for early termination. Notably, we establish MOAOO as the inaugural multi-objective variant of AOO, integrating dynamic elite retention strategies, non-dominated sorting, and dynamic archive mechanisms to enable effective collaborative optimization of three conflicting goals. Enough experiments on ZDT test functions demonstrate that the designed MOAOO method shows competitive performance compared to advanced algorithms such as Pre-DEMO, MOEA/D-OED, and Pi-MOEA in terms of hypervolume inverted generational distance and the Spacing metrics. The indicator is improved in certain configurations. In an engineering case study, MOAOO reduces resource fluctuation by 72.7% in the compromise solution while achieving a balanced duration (279days) and cost ($1.34M). Moreover, the proposed algorithm converges in 118 iterations on average, thereby verifying its practical value in construction scheduling.

BackgroundA study was conducted to examine the impact of Internet use on the mental health of male and female older adults with different migration statuses living in rural China.MethodsData came from the China Family Panel Studies (CFPS) 2020. The propensity score matching method was adopted to analyze the effect of Internet use on mental health of rural older adults as a function of migration status and gender.ResultsOur findings indicated a progressive decline in depressive symptoms and a corresponding increase in mental well-being among older migrants, left-behind older adults, and those without migrant children. Furthermore, the mental health benefits associated with Internet use increased alongside this improvement. Importantly, older migrant women derived fewer mental health benefits from Internet use than their male counterparts, as did left-behind older women relative to men in the same cohort.ConclusionSince the mental health of the older migrants was worse than that of left-behind older adults or those without migrant children, and older migrant women derived fewer mental health benefits from Internet use than their male counterparts, it is necessary to pay more attention to rural older migrants, especially older women, to improve their willingness and ability to use the Internet.

Against the backdrop of accelerating global climate change and urbanization, urban land cover change has emerged as a critical indicator for understanding the dynamic evolution of cities and the transformation of urban ecosystems. This study proposes a data-driven framework for fine-scale urban land cover change assessment based on the UASFNet model, enabling high-precision evaluation of urban land cover dynamics. The approach first performs preprocessing and co-registration of bi-temporal remote sensing images from the study area, and applies the trained UASFNet model to identify urban land cover types and extract land cover information for each temporal phase. The Analytic Hierarchy Process (AHP) is then employed to determine the weights of various indicator factors. By integrating building disturbance, greenbelt disturbance, and road disturbance indices, the framework quantitatively evaluates the intensity of land cover change at both pixel and regional scales. Experimental results across three benchmark datasets, consisting of high-resolution sub-meter RGB urban remote sensing imagery, demonstrate that UASFNet achieves superior segmentation accuracy, with mean Intersection over Union (mIoU) values of 91.52%, 93.31%, and 88.90%, substantially outperforming several state-of-the-art baseline models. Spatial analysis of the Langfang urban area (2017-2023) reveals a marked increase in impervious surface coverage (+16.86%) and a sharp decline in greenbelt (-40%), with the urban landscape exhibiting a multi-core, belt-like expansion pattern oriented toward newly developed districts. The proposed framework not only enhances the interpretability and generalization of remote sensing models in complex urban environments but also provides a scalable analytical tool to support urban spatial planning, ecological conservation, and sustainable city governance.

The paper investigates the correlation of consumer price index with labour force participation and economic growth in India between 2017 to 2024. The analysis involves using secondary data that is sourced from the Ministry of Labour and Employment, the World Bank, the Ministry of Education and Macro trends to explore the effect of the rural and urban labour force participation rates between males and females, their enrolment in secondary schooling, total and planned spending on education and the yearly increase in the GDP on consumer price movements. Since the consumer price index data is non-negative and skewed and the time-series sample used is rather small, Poisson regression is the model used as the major econometric tool. The findings show that the result is high heterogeneity of labour market segments. Male labour force participation in the rural areas has a positive and significant relationship with the consumer price index and a negative significant relationship with female labour force participation. The variables of urban labour force participation are statistically insignificant and there are weaker or less predictable relationships with the price movements. The increase in the gross domestic product is observed to significantly affect the consumer price index negatively, which implies a higher rate of economic growth could alleviate the inflation pressure. The results reveal the significance of the demographic and sectoral differences in the study of the dynamics of inflation and offer policy-related details on labour participation and growth in the determination of price stability.