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Identity Resocialization: The Returning Phenomenon of Migrant Workers under Rural Revitalization in Liaoning, China
Full text linkIn 2017, China initiated the Rural Revitalization Strategy (RSS) to revive rural regions. It aims to revitalize rural areas and the farming sector through modernization and infrastructure enhancement. This led to the return of many migrant workers. This study examines the economic opportunities available to returning migrants in Liaoning, analyzes their success rate in terms of integration, and highlights the challenges they face during resettlement. The study entailed a secondary data analysis, and the data were analyzed using statistical tools and SPSS software. The study found that migration was influenced by education and its role in economic opportunity. Employment status was found to be a significant factor in economic opportunity, particularly in the labor market. Notably, the majority of migrants chose to remain in Liaoning, suggesting that rural rehabilitation initiatives had been effective. The findings highlight the complex reintegration processes of returning migrants and underscore the need to understand these dynamics for effective policymaking
Do Populists in Power or the Economy Impact Civic Culture?
Full text linkThis paper empirically tests whether populists in power or economic wellbeing influence civil society and civic culture. It conceptualizes civic culture broadly by focusing on citizen mobilization and evaluation of both national and supranational political institutions. The longer populists hold government positions, the stronger their control over civil society organizations, affecting participation in civil society initiatives. However, a higher GDP per capita is associated with increased participation in civic society initiatives. Both the duration of populist rule and economic factors shape civic culture across Central and Eastern Europe. On the country level, the length of governance under populist elites correlates with a decrease in individual social connectedness, growing dissatisfaction with democracy, and diminished interest in politics. Country-level economic development correlates with higher levels of institutional trust, social trust, social connectedness, and satisfaction with democracy but negatively with trust in the European Union, election turnout, interest in politics, and participation in trade unions. Higher levels of civic culture are most consistently driven by one's income at individual level. Citizens appear to be evolving into allegiant citizens-those who maintain some level of trust in governmental institutions also support the principles and practices of democracy and exhibit a general increase in apathy toward politics. Evidence from the European Social Survey and the V-Dem database supports these conclusions
GPT-based lifelong learning and ANFIS-driven reply memory ratio prediction for aspect-based sentiment analysis
Full text linkGPT is among the most powerful large language models (LLMs), known for its versatility and strong performance across a wide range of tasks. However, its substantial computational demands and limited cross-domain generalization present challenges, particularly in resource-sensitive applications like Aspect-Based Sentiment Analysis (ABSA). Existing ABSA models are typically domain-specific and suffer from catastrophic forgetting - losing previously acquired knowledge when sequentially trained on new domains - resulting in poor scalability and knowledge retention. To address these issues, we proposed a novel framework that integrates GPT-2 with a replay-based lifelong learning mechanism to support incremental, multi-domain ABSA while mitigating forgetting. The model is sequentially fine-tuned using real-data replay across four diverse ABSA domains: Laptops, Restaurants, Tweets, and Finance. Experimental results show that proposed model achieves an average accuracy of 0.85 and a Backward Transfer (BWT) score of -0.09, significantly outperforming the baseline model without lifelong learning (accuracy of 0.70, BWT of -0.64). We further conducted a t-test to validate the statistical significance of the improvements. we design an ANFIS-based model trained on experimental results to predict the proper memory ratio for new datasets, enabling more effective and adaptive lifelong learning in GPT-based architectures. In addition, we applied a multi-level data augmentation pipeline, which significantly improved performance across domains (p = 0.0049), enhancing both retention and generalization under constrained memory. Additionally, we introduced a domain sequence permutation study to test robustness against task-order sensitivity, while another part evaluates generalization under a simulated fifth domain constructed from a mixture of all original domains. These components validate the model’s scalability and ability to generalize beyond trained distributions. An ablation study was conducted to isolate the contributions of each module, including replay, ANFIS prediction, and data augmentation. The results demonstrate that removing any single component leads to a measurable drop in performance, confirming that each part of the framework contributes meaningfully to overall effectiveness. A post-hoc comparison with a distillation-based lifelong learning baseline was conducted, showing improved performance of our replay + ANFIS approach. We acknowledge that additional comparisons with advanced baselines such as GEM or A-GEM are needed to further strengthen this claim, which we leave for future work. Overall, this study demonstrates the effectiveness of combining GPT-2 with replay-based lifelong learning and adaptive memory control, offering a scalable and robust solution for continuous, multi-domain sentiment analysis. Our proposed model provides a practical foundation for future research in dynamic, cross-domain ABSA systems
GDP per Capita and Human Capital Investment in Five Countries after Exhaustion of the First Demographic Dividend
Full text linkAs total fertility rates (TFRs) decline globally and life expectancy rises, population aging presents significant economic challenges, including a shrinking working-age population and slower economic growth. This paper examines the impact of aging on economic growth trajectories in China, Hungary, Italy, Sweden, and the Republic of Korea, exploring how differing aging patterns influence economic outcomes. Using a general equilibrium model where agents optimize over an infinite horizon, the study projects GDP per capita and per worker over 60 years. The selected countries, each with TFRs below the replacement level for over three decades, are grouped based on demographic aging indicators. GDP trajectories are shaped by the ratios of the older and young populations to the working-age group and changes in workforce size. Human capital investment is a key component of the model, as each child, while they are young, receives human capital investment every year. This investment determines their future productivity in the workforce and, consequently, the productivity of the overall economy. To our knowledge, no prior research has examined human capital investments across multiple periods in models with infinitely optimizing agents and their cumulative impact on economic productivity. The findings suggest that aging trajectories significantly shape economic growth paths, underscoring the need for tailored strategies to sustain growth in different demographic contexts
Public procurement cartels : a large-sample testing of screens using machine learning
Full text linkDue to the high budgetary costs of public procurement cartels, it is crucial to measure and understand them. The literature developed screens that work well for selected cartel types and with high quality data, but it didn’t produce generalisable knowledge supporting policy and law enforcement on typically available datasets. We simultaneously measure multiple cartel behaviours on publicly available data of 73 cartels from 7 European countries covering 2004-2021. We apply machine learning methods, using diverse cartel screens characterising pricing and bidding behaviours in a predictive model. Combining many indicators in a random forest algorithm achieves 70-84% prediction accuracy, distinguishing behavioural traces of confirmed cartels from non-cartels across different cartel types and countries (accuracy is 97% when trained and tested on a single cartel case, typical of the literature). Most screens contribute to prediction in line with theory. These results could improve cartel detection and investigations and support pro-competition policies
Assessing Climate Preparedness : A Comparative Analysis of Canada's Provinces and Municipalities
Full text linkClimate change poses environmental, economic, and societal risks to Canada, as evidenced by the increasing severity and frequency of wildfires, floods, and storms. While climate mitigation efforts remain paramount, this study underscores the urgent need for improved data transparency to enable better assessments and facilitate more comprehensive adaptation efforts. We assess the preparedness of ten Canadian provinces and six municipalities for climate-related natural disasters by developing a composite index (score) that integrates both financial and qualitative indicators derived from public disclosures. During our analysis, we encountered persistent gaps in natural disaster damage reporting and noted a lack of standardized data-shortcomings that obstruct accurate benchmarking and hinder informed decision-making. We thus provide recommendations for enhanced reporting that can not only guide policymakers and community planners but also support investors in evaluating climate resilience as a factor in their capital allocation and risk assessments. By aligning adaptation strategies with regional risk profiles, ensuring greater data comparability, and integrating resilience metrics into investment criteria, stakeholders can more effectively navigate the evolving landscape of climate-related threats and foster a more adaptable, future-ready Canada
Anti-Corruption Reforms in Ukraine: Institutional Progress and Public Perception in the Context of EU Integration
Full text linkCorruption has long been one of Ukraine’s most pressing issues, imposing significant costs on the state budget, businesses, and citizens while discouraging investment and undermining the rule of law. Combating corruption is also essential for Ukraine’s EU integration, given that compliance with anti-corruption standards is a core accession requirement. This article explores the evolution and effectiveness of Ukraine’s anti-corruption reforms in the context of European integration. It analyses the historical and structural features of corruption in Ukraine and identifies its dominant form as being driven by the elite. Using a combination of policy analysis alongside public opinion data, the study evaluates the implementation of reforms and how society perceives their impact. Despite notable institutional progress, public trust remains limited, highlighting a discrepancy between formal advancements and citizens’ perceptions. By comparing reform outcomes with public opinion, the article highlights the crucial role of civil society and businesses in sustaining anti-corruption efforts and provides policy recommendations to strengthen public credibility and ensure the long-term success of reforms. The recent controversy surrounding Law No. 12414, which temporarily undermined the independence of Ukraine’s key anti-corruption bodies, highlights the importance of robust anti-corruption frameworks and an engaged civil society
Preferences of Rural Travelers Towards Demand Responsive Transport
Full text linkDemand responsive transport (DRT) has received significant attention in recent years as a transport mode that can bridge the gap between personal motorized travel and public transport. It combines the best of individual cars and public transport: it can be more flexible, than traditional public transport, resembling the convenience of owning a car, but it does not come with the high cost of owning and maintaining a vehicle for the user. We conducted a stated preference (SP) survey about potential users’ preferences towards demand responsive transport at a rural Eastern European town in Hungary, Kiskunhalas, Hungary, and modelled individuals’ preferences towards DRT using a multinomial logit model. We had 6012 responses from a sample of 501 individuals, that was representative of the settlement with respect to age and gender. The results show that all else being equal, individuals find the DRT service the second most attractive mode of transport after cycling, meaning that a DRT service could have a potentially large uptake in the population. Our results could be used by decision makers and service providers for the design of a DRT service. © The Author(s) 2025
“My Little Son, My Everything” : Comparative Caregiving and Emotional Bonds in Dog and Child Parenting
Full text linkDogs are often viewed as family members, and many owners describe them as “fur babies.” However, little is known about how women with and without children perceive and practice caregiving toward their dogs, and how these experiences relate to parenting. This qualitative study explored the meanings of dog and child caregiving among 28 dog-owning women (13 mothers and 15 childless) through semi-structured interviews. All participants had lived with their dog for at least one year. Thematic analysis identified five main themes: (1) emotional meanings and motivations of caregiving, (2) practical caregiving and daily routines, (3) responsibility and dependency, (4) social relationships and support, and (5) life course perspectives. Both mothers and non-mothers described their dogs as sources of joy, companionship, and unconditional love. Women without children often saw their dogs as child substitutes, while mothers stressed the greater responsibility and permanence of raising children. Dog ownership and parenting influenced social life and work differently: dogs often increased social interaction and offered flexibility, whereas children introduced stricter routines and reduced spontaneity. Overall, dogs fulfilled important emotional and caregiving needs, particularly among women without children, but did not replace the unique social and moral responsibilities of parenting
A szíriai belső menekültek helyzete az Aszad-rezsim utolsó időszakában : hazatérés és újrakezdés Szíriában
Full text linkA 2011-es „arab tavasz” folytatásaként kibontakozott szíriai polgárháború következményeként a nemzetközi közösség 2012-ben visszavonta a Bassár al-Aszad vezette kormány elismerését, s ennek velejárójaként az Arab Liga felfüggesztette az országnak a szervezetben való tagságát. Mintegy hétmillió ember kényszerült elhagyni a hazáját, ami Európa és a térség egyik legnagyobb menekültválságát idézte elő, de az országon belül is nagyjából hétmillióra tehető azoknak a száma, akiknek muszáj volt elhagyniuk az otthonukat, s váltak ún. belső menekültekké. Bár a 2020-as évek elején úgy tűnt, hogy a szíriai belpolitikai helyzet nyugvópontra jut, sőt 2023-ban Szíriát visszafogadták az Arab Ligába is, azonban a 2024 végén lezajlott váratlan és hirtelen események, az Aszad-rendszer bukása az ország teljes átalakulására utal. A politikai átrendeződés mellett a politikusok és a szakértők is kevesebb figyelmet szentelnek a társadalomban bekövetkező változásokra, amelyek fő kérdéseként a külső menekültek repatriálása és annak körülményei jelennek meg. Ugyanakkor szinte teljesen elsikkad a belső menekültek hazatérésének a kérdése és programja. A jelen tanulmány egy, az ő önkéntes hazaköltözésük elősegítésére indított nemzetközi fejlesztési együttműködés keretében végrehajtott programot, valamint annak a lehetőségeit és a nehézségeit kívánja bemutatni egy elsősorban keresztények alkotta 225 fős mintán keresztül. A Homsz városában végzett kutatás eredménye megerősíti azon korábbi visszajelzéseket, hogy a belső menekültek nem kívánják átlépni az országhatárokat, továbbá rámutat a makroszinten ismert, a súlyos gazdasági helyzettel és a közszolgáltatások alacsony színvonalával kapcsolatos problémákra