Identifying the roots of inequality of opportunity in South Korea by application of algorithmic approaches

This study identifies the roots of inequality of opportunity in South Korea using algorithmic approaches on survey data. Unlike previous studies focusing on measuring inequality, this research estimates the importance of variables to pinpoint its origins. Decision tree classification, LightGBM, and SHAP are applied to analyze the data. Results indicate that the region of upbringing, gender, and father's occupation are key factors contributing to inequality of opportunity, highlighting regional disparities and the perpetuation of gender inequality through social environment and paternal background.

Seungwoo Han