The Analysis of the Global Gender Gap in OECD Countries by Data Mining

Abstract

The Global Gender Gap Index is a performance-based measure that assesses gender inequality across four key dimensions, independent of a country’s level of economic development. The Global Gender Gap Index, prepared by the World Economic Forum, evaluates countries according to sub-dimensions of economic participation and opportunity, educational attainment, health and survival, and political empowerment. The World Economic Forum reports on countries' success or failure in closing the gender gap, and country rankings are determined based on this report. This study employs cluster analysis, a widely used data mining technique, to examine the 2023 Global Gender Gap Index data for OECD countries. The analysis groups countries into three distinct clusters based on their similarities. Unlike previous studies, this research applies four different clustering algorithms and presents the results separately for each approach. Among these, the Canopy algorithm yielded the highest Silhouette score (0.3948), indicating superior clustering quality compared to the other methods. Consequently, the analysis and interpretations are based on the findings of the Canopy algorithm. The findings reveal that OECD countries can be classified into three distinct clusters, with women’s economic participation and political empowerment emerging as the primary determinants of cluster similarities and differences. These insights offer valuable contributions to researchers and policymakers, facilitating the development of more comprehensive and effective strategies to promote gender equality.