In a context of refugee precarity, the article highlights the significance of inclusive economic models for sustainable resilience amidst protracted crises, examining the interplay between humanitarian aid and economic development within the Minawao camp. Initially established as a temporary solution, the camp now shelters over 76,000 Nigerians fleeing Boko Haram violence. The study focuses on analyzing initiatives implemented to promote economic empowerment and resilience for refugees within a sustainable humanitarian framework. Through a combination of survey data, document reviews, and interviews, findings reveal that while these initiatives align with Sustainable Development Goal 8, they remain limited and insufficiently adapted to the skills and needs of the refugees. The camp’s geographic isolation and the passive involvement of the Cameroonian government further exacerbate the refugees’ dependency on humanitarian aid. Consequently, the study advocates for greater host-state involvement beyond theoretical agreements, the diversification of economic opportunities beyond the camp, adjustment of empowerment programs to meet refugee needs, and strengthened funding through innovative partnerships.

Demographic policy is one of the key tasks of almost any state at the present time. It correlates with the solution of pressing problems in the economic and social spheres, directly depends on the state of healthcare, education, migration policy and other factors and directly affects the socio-economic development of both individual regions and the country as a whole. Many Russian and foreign researchers believe that demographic indicators very accurately reflect the socio-economic and political situation of the state. The relevance of the study is due to the fact that for the progressive socio-economic development of any country, positive demographic dynamics are necessary. The main sign of the negative demographic situation that has developed in modern Russia and a number of countries, primarily European, is the growing scale of depopulation (population extinction). The purpose of this work was to analyze the existing demographic policy of Russia and compare demographic trends in Russia and other countries. The work uses methods of statistical data analysis, comparison of statistical indicators of fertility, mortality, natural population decline, migration, marriage rates in Russia and the Republic of Srpska, methods of retrospective analysis, research of the institutional environment created by the action of state and national programs “Demography”, “Providing accessible and comfortable housing and public services for citizens of the Russian Federation”, “Strategy of socio-economic development for the period until 2024”, Presidential decrees, etc. Research has shown that despite measures taken to overcome the demographic crisis, Russia’s population continues to decline. According to the Federal State Statistics Service of the Russian Federation (Rosstat), as of 1 January 2023, 146.45 million people lived in Russia. By 1 January 2046, according to a Rosstat forecast published in October 2023 the country’s population will decrease to 138.77 million people. To solve demographic problems in the Russian Federation, a national project “Demography” was developed and approved. The government has allocated more than 3 trillion rubles for its implementation. However, it is not possible to completely overcome the negative trend. The authors proposed a number of economic and ideological measures within the framework of agglomeration, migration, and family support policies that can be used within the framework of socio-economic development strategies and national programs aimed at overcoming the demographic crisis.

This study examines the interaction between foreign direct investment (FDI), idiosyncratic risk, sectoral GDP, economic activity, and economic growth in ASEAN countries using structural equation modeling (SEM) performed using AMOS software. The analysis uses data from the ASEAN Statistics Database 2023 to distinguish the significant direct and indirect impacts of FDI on idiosyncratic risks, sectoral GDP, economic activity and aggregate economic growth can. ASEAN, which includes ten Southeast Asian countries, has experienced rapid economic growth and increasing integration in recent decades, making it an interesting area to study these relationships. The study covers a comprehensive period to capture trends and differences among ASEAN member states. Applying SEM with AMOS allows a detailed examination of complex relationships between important economic variables. The results show a clear link between FDI inflows, idiosyncratic risks, industry GDP performance, economic activity, and overall economic growth. More specifically, FDI inflows have a notable direct influence on idiosyncratic risks, which then impact GDP growth by sector, and the level of economic activity and ultimately contribute to economic growth trends. economy more broadly in ASEAN countries. These findings highlight the importance of understanding and effectively managing the dynamics between FDI and various economic indicators to promote sustainable economic development across ASEAN. This information can inform policymakers, investors, and stakeholders in developing targeted strategies and policies that maximize the benefits of FDI while minimizing related risks to promote strong and inclusive economic growth in the region. This study highlights the multifaceted relationships in the ASEAN economic context, emphasizing the need for strategic interventions and policy frameworks to exploit the potential of foreign investment directed at ASEAN, to the Sustainable Development Goals and long-term economic prosperity in the region.

This study delves into the role of pig farming in advancing Sustainable Development Goal (SDG) 8—Decent work and economic growth in Buffalo City, Eastern Cape. The absence of meaningful employment opportunities and genuine economic progress has remained a significant economic obstacle in South Africa for an extended period. Through a mixed-method approach, the study examines the transformative impact of pig farming as an economic avenue in achieving SDG 8. Through interviews and questionnaires with employed individuals engaged in pig farming in Buffalo City, the study further examines pig farming’s vital role as a source of decent work and economic growth. The study reveals inadequate government support and empowerment for pig farming in Buffalo City despite pig farming’s resilience and potential in mitigating socio-economic vulnerabilities and supporting community’s livelihoods. To enhance pig farming initiatives, this study recommends government’s prioritization of an enabling environment and empowerment measures for the thriving of pig farming in Buffalo City. By facilitating supportive policies and infrastructures, the government can empower locals in Buffalo City to leverage pig farming’s potential in achieving SDG 8.

The paper considers an important problem of the successful development of social qualities in an individual using machine learning methods. Social qualities play an important role in forming personal and professional lives, and their development is becoming relevant in modern society. The paper presents an overview of modern research in social psychology and machine learning; besides, it describes the data analysis method to identify factors influencing success in the development of social qualities. By analyzing large amounts of data collected from various sources, the authors of the paper use machine learning algorithms, such as Kohonen maps, decision tree and neural networks, to identify relationships between different variables, including education, environment, personal characteristics, and the development of social skills. Experiments were conducted to analyze the considered datasets, which included the introduction of methods to find dependencies between the input and output parameters. Machine learning introduction to find factors influencing the development of individual social qualities has varying dependence accuracy. The study results could be useful for both practical purposes and further scientific research in social psychology and machine learning. The paper represents an important contribution to understanding the factors that contribute to the successful development of individual social skills and could be useful in the development of programs and interventions in this area. The main objective of the research was to study the functionalities of the machine learning algorithms and various models to predict the students’s success in learning.