How do people understand inequality in Chile? A study through attitude network analysis

Abstract

This article constitutes the first application of the attitude network approach to peoples' views on inequality. We adopt a network model in which nodes represent survey variables and edges their conditional associations. This allows us to conceptualize perceptions, beliefs, and judgments about inequality as a network of connected evaluative reactions. We analyze data from the 2019 ISSP Social Inequality Module for Chile, one of the most unequal countries in the world. Relying on a network approach, we systematically analyze the wide-ranging indicators measuring subjective inequality. Results show that conceptions regarding inequality, redistribution, taxation, and wages form a moderately connected unified belief system with a small-world structure. In addition, we stratify the sample by education, income, and social class, obtaining six attitude networks. We compare the structures of these networks, investigating differences in community membership, node centrality, and network connectivity, evidencing that people in lower social positions have a more multidimensional understanding of inequality. Our work contributes to social justice research by proposing an innovative conceptualization of these attitudes and providing evidence of their structural variation across different socioeconomic groups.

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