Regional Perspectives of Rural Development in Latin America and the Caribbean: A Contextualized Framework Tested by Clustering Analysis

Abstract

Understanding the contextual dynamics of development projects is essential for achieving effective and sustainable outcomes. While existing frameworks provide guidance for translating rural development concepts into structured thematic areas and indicators, they often lack specificity to regional characteristics. This limitation is particularly evident in regions like Latin America and the Caribbean (LAC), where diverse socioeconomic and geographical contexts demand tailored approaches. Here, we developed a dedicated framework designed to capture the unique features of the LAC region. It is structured around four dimensions, 14 themes, and 33 parameters, providing a comprehensive foundation for planning and evaluating rural development initiatives. To operationalize this framework, we employed machine learning techniques to group countries based on shared characteristics and similarities, enabling an unbiased identification of key dimensions. Our analysis identified eight clusters, some reflecting geographical coherence—such as island nations in the Caribbean and countries in northern Central America—while others revealed unexpected groupings, including Brazil with Ecuador and Panama. These results underscore the utility of the framework in uncovering both intuitive and novel insights. This contextualized framework offers a robust reference tool for exploring rural development in LAC, facilitating evidence-based planning and fostering a deeper understanding of the region's diverse rural contexts.