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.
This research uses both quantitative and qualitative research methodologies to examine the complex factors affecting community resilience in various settings. In this case, the research explores how social cohesion, governance effectiveness, adaptability, community involvement, and the specified difficulties influence resilience results by using the five pillars of resilience as variables. Descriptive and inferential statistics are used to test hypotheses on the relationships between social cohesion, governance effectiveness, adaptive capacity, and community resilience variables. Qualitative data provides further insights into the quantitative results by providing broader views and experiences of the community. The study shows how social capital is important in increasing community capacity, stressing the importance of social relations and trust in developing community solutions to disasters. Another major factor that stands out is the governance factor that ensures that decisions are made, and actions taken in line with the community’s best interest in improving its ability to prepare for and respond to disasters. Adaptive capacity is seen as a key component of resilience and this paper emphasizes the importance of communities to come up with measures that can be adjusted to the changing circumstances. In summary, this study enriches theoretical understanding and offers practical applications of the processes that can enhance community resilience based on the principles of social inclusion, sound governance, and context-specific solutions.
Political representation is responsible for choices regarding the supply and the management of transport infrastructure, but its decisions are sometimes in conflict with the will and the general interest expressed by citizens. This situation has progressively prompted the use of specific corrective measures in order to obtain socially sustainable decisions, such as the deliberative procedures for the appraisal of public goods. The standard Stated Choice Modelling Technique (SCMT) can be used to estimate the community appreciation for public goods such as transport infrastructure; but the application of the SCMT in its standard form would be inadequate to provide an estimation that expresses the general interest of the affected community. Hence the need to adapt the standard SCMT on the basis of the operational conditions imposed by deliberative appraisal procedures. Therefore, the general aim of the paper is to outline the basic conditions on which a modified SCMT with deliberative procedure can be set up. Firstly, the elements of the standard SCMT on which to make the necessary adjustments are identified; subsequently, modifications and additions to make to the standard technique are indicated; finally, the contents of an extensive program of experimentation are outlined.
Community policing has emerged as a vital instrument for combatting crime and enhancing public safety in South Africa. As a result, it has the capacity to go beyond traditional law enforcement functions as a mediator in disputes, fostering improved relationships between the police and the communities where they work. This paper analyses the implementation of community policing strategies by the South African police with the purpose of resolving conflicts. This study aims to address social crime prevention-related concerns through community policing methods in the Galeshewe police area within the Francis Baard policing regions of the Sol Plaatje Municipality, South Africa. The paper examines the tactics that community police employ to enforce the law, avoid social issues, and manage conflict resolution in the communities. A qualitative method and descriptive design were employed. Comprehensive document analysis, semi-structured interviews, and observations were employed as data collection strategies. An inductive reasoning model was used to analysis data. The findings of the study demonstrated that community policing plays an important role in optimizing problem mapping and it increases public knowledge of the importance of upholding security and order in the different police operations that support the community policing program.
Climate change is a pressing global challenge that requires immediate action. To address this issue effectively, it is essential to engage and empower the younger generation who will shape the future. This abstract presents the experience of Mohamed Bin Zayed University for Humanities (MBZUH) in UAE in promoting climate action through youth empowerment and environmental education.MBZUH has recognized the significance of incorporating environmental education into its curriculum to foster a generation of environmentally conscious individuals. Through a multidimensional approach, the university has developed innovative strategies to empower students, enabling them to become active participants in addressing climate change. These strategies encompass both formal and informal education, leveraging various platforms and partnerships to create a comprehensive learning environment.This study delves into the initiatives undertaken by MBZUH to empower youth in climate action. It explores the incorporation of environmental education across disciplines, integrating sustainability principles into existing courses, and offering specialized programs focused on environmental science and climate studies. Additionally, it highlights the university's efforts in promoting hands-on learning experiences, such as field trips, research projects, and community engagement, to deepen students' understanding of climate issues and inspire practical action.Furthermore, the study examines the role of MBZUH's collaboration with local and international organizations, governmental bodies, and the wider community in fostering youth empowerment and climate action. It showcases successful partnerships that have resulted in impactful initiatives, including awareness campaigns, capacity-building workshops, and youth-led environmental projects.By sharing the experience of MBZUH, this study aims to provide valuable insights and best practices for promoting climate action through youth empowerment and environmental education. It underscores the importance of empowering the next generation with the knowledge, skills, and motivation to become effective agents of change in addressing climate challenges.
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