This is a review of empirical studies with the objective of analyzing the theoretical-practical discussions that have been raised internationally to deepen the understanding of the access of rural youth to higher education as an object of study. For this purpose, a narrative review was designed, considering scientific articles published in three different languages and concerning studies conducted in 21 different countries in all regions of the world. The results reveal three discussions: a) the strong interest that higher education has regained in the life expectations of rural young people and their families, especially as a means of social advancement; b) the inequalities that most affect the access of rural youth to higher education are the lack of academic offerings in rural areas and the discontinuities that occur around rural socio-cultural capital; c) since the inequalities experienced by rural youth are diverse, actions to promote greater democratization cannot be limited to implementing systems of grants and scholarships. It is concluded that the major project consists of creating a differentiated higher education model that, in terms of location, academic offerings, recognition of knowledge, and articulation with the environment, allows rural youth to experience their professional training not as an inevitable process of acculturation, but as a continuation of their socio-cultural capital and their territorial yearnings.

Presently, any development initiatives without considering sustainability can barely be imagined. There has been a paradigm shift in the focus of the development partners from the mere development to sustainable development. However, the role of development partners in bringing sustainability in livelihood assets of the rural community has long been questioned. Hence, this study aims to explore the sustainability in the form of changes in livelihood assets of a local community in Bangladesh. This study considers the changes in livelihood assets of the community over the three-time frames - before, during, and after a project implemented by a national NGO called ‘UST’ and subsequently identifies the community’s capacity to sustain the project outcomes after the completion of the project. ‘Sustainable Livelihood Framework (SLF)’ developed by Department for International Development (DFID) was utilized in this study to analyse the vulnerability and livelihood issues of the community members. Data has been collected through focus group discussions, household survey and key informants’ interviews from three distinct villages of ‘Khutamara’ union in the ‘Nilphamari’ district of Bangladesh. The finding of the study states that all the livelihood assets such as the social capital, human capital, natural capital, financial capital, physical capital have positively changed due to the interference of the development partners. This study further finds that even after the completion of project tenure, such positive trends continue to exist among the community members indicating sustainable development. Moreover, political capital- a new type of livelihood has also emerged because of the project implementation which was not quite evident before the inception of the project. In addition, this study explored the unique phenomenon of the Shabolombee Gram, where the transformation altering farmers’, livelihoods does not come from the government or the private sector but originates from a Non-Governmental Organization (NGO). Therefore, the government and its development partners may adopt and incorporate the Modified Sustainable Livelihood Framework (MSLF) to ensure the sustainable development.

This study examines the contentment and commitment of rural residents from three different perspectives. The first is environmental management, followed by municipal services and finally territorial planning. The study’s objective is to analyze the causal relationships between the expected quality and perceived quality concerning perceived value, satisfaction and citizen loyalty to provide tools for decision-making to public managers. This research proposes a structural equation model to evaluate and validate five hypotheses. For this study, household-level surveys were implemented to a population sample of 450 families in the rural area of Tenguel in Ecuador. The results suggest that the public policies exercised by territorial managers significantly influence citizens’ perceived value, satisfaction, and loyalty, which impacts social welfare. This research shows that there are deficient areas that negatively impact perceived locality, which decreases the perceived value. Such as firefighting service, municipal police, veterinary services, preservation of historical and cultural assets and activities, and facilities for community use.

The lack of attention from mining companies to the majority of areas still affected by mining activities can result in regional economic disparities and high levels of social violence. It is crucial to have policy strategies for mining contributions to rural development equity and social violence reduction through CSR assistance and other aid funds. This research employs the Multi-Criteria Decision Analysis method using the MULTIPOL analysis tool. Recommended action programs include the construction of schools, provision of scholarships, job openings, business capital, and infrastructure development, supported by strong regulations and law enforcement. Cracking down on illegal mining permits is essential to reduce environmental damage. Holistic and sustainable integration policies, alongside effective law enforcement, are necessary to achieve the goals of equitable development and social violence reduction. These steps should be reinforced with incentives for traditional/community leaders and increased police/military presence in villages within the next 2 years, particularly in zones 2 and 3 of the mining areas. Failure to implement these measures could escalate social violence, jeopardize security, and impede the operations of mining companies in Kolaka. The findings of this research support the priority of security and orderliness in development and underscore the importance of diverse research methods for mining area development policies.

This study aimed to determine the socio-economic poverty status of those living in rural areas using data surveys obtained from household expenditure and income. Machine learning-based classification and clustering models were proven to provide an overview of efforts to determine similarities in poverty characteristics. Efforts to address poverty classification and clustering typically involve comprehensive strategies that aim to improve socio-economic conditions in the affected areas. This research focuses on the combined application of machine learning classification and clustering techniques to analyze poverty. It aims to investigate whether the integration of classification and clustering algorithms can enhance the accuracy of poverty analysis by identifying distinct poverty classes or clusters based on multidimensional indicators. The results showed the superiority of machine learning in mapping poverty in rural areas; therefore, it can be adopted in the private sector and government domains. It is important to have access to relevant and reliable data to apply these machine learning techniques effectively. Data sources may include household surveys, census data, administrative records, satellite imagery, and other socioeconomic indicators. Machine learning classification and clustering analyses are used as a decision support tool to gain an understanding of poverty data from each village. These strategies are also used to describe the profile of poverty clusters in the community in terms of significant socio-economic indicators present in the data. Village clusters based on an analysis of existing poverty indicators are grouped into high, moderate, and low poverty levels. Machine learning can be a valuable tool for analyzing and understanding poverty by classifying individuals or households into different poverty categories and identifying patterns and clusters of poverty. These insights can inform targeted interventions, policy decisions, and resource allocation for poverty reduction programs.