Do People Still Perceive Korea As Meritocratic Society? Changes of Meritocratic Perception Among South Korean Youth, 2009-2021
Monday, 7 July 2025: 00:00
Location: SJES021 (Faculty of Legal, Economic, and Social Sciences (JES))
Oral Presentation
Jungjin KIM, Ewha Womans University, Republic of Korea
Minzee KIM, Ewha Woman's University, Republic of Korea
SetByol CHOI, Ewha Womans University, South Korea
For a long time, Korean society has had meritocratic perception toward success, which implies people can get ahead by their individual merits. However, due to the exacerbation and adhesion of economic inequality and triggered people to perceive that background factors, such as family’s wealth, are being more important to get ahead, even though some studies show economic inequalities haven’t been worsened seriously. In addition, perceptions of structural discrimination also has been arisen, which were overlooked by meritocratic ideology, showing not only meritocratic factors are important for economic triumph, but also other dimensions. But however other factors matters, it doesn’t suggests the fall of meritocratic perception. Rather, it can be said that all of the dimensions are becoming important to get ahead. This matters for entire society, and especially for the youth because it has a possibility of deep correlation of people’s motive to economic activities, which can become a base of society being dynamic or static.
From according background, this study aims to answer two questions focused on the youth: A. How the perception of getting ahead in Korea has been changed? and B. What variables do affect? Using Korean General Social Survey data(KGSS) during 2009, 2014, and 2021, this study tries to answer the questions by following strategies. First, to define the classes of getting ahead perceptions and investigate their characteristics, the study classifies five types of perception of getting ahead using factor analysis and cluster analysis. Chi-square analysis is used to check whether some socio-demographic variables are distributed notably different, thus explaining each cluster’s feature. After, it analyzes what variables affect the possibility of being affiliated to each clusters using multi-logistic regression. The study analyzes significant insights and discuss conclusions.