From Category to Conflict: Increasing Representational Complexity as a Cognitive Approach to Reducing Intergroup Bias

Social categorization is a fundamental cognitive process that enables individuals to efficiently navigate complex social environments. However, the same mechanism that facilitates cognitive efficiency can also contribute to the formation of stereotypes, prejudice, and intergroup conflict. Approaches to reducing intergroup bias have often focused on specific interventions, such as individuation, intergroup contact, and multiple-categorization, yet these approaches are typically discussed within separate theoretical frameworks. The present review argues that these interventions may be understood through a common cognitive mechanism: increasing representational complexity in social perception. Drawing on theories of categorization, social categorization, and intergroup relations, we first review how category-based processing contributes to the emergence of intergroup bias and conflict. We then examine the Continuum Model of Impression Formation and dual-process accounts of social cognition, which suggest that perceivers can move from category-based judgments toward individuated perceptions when sufficient information, attention, and motivation are available. Building on this framework, we review individuation interventions, multiple categorization and intergroup contact. Although these approaches differ in implementation, each may reduce reliance on simplistic social categories by increasing the amount and complexity of information available about others. We argue that representational complexity provides a useful integrative framework for understanding how diverse interventions reduce intergroup bias and conflict. Rather than attempting to eliminate categorization, effective interventions may reduce intergroup bias by increasing the complexity of social representations and promoting more differentiated and individuated understandings of others.

کلیدواژه ها:

Categorization ، Individuation ، Intergroup Bias ، Multiple Categorization ، Representational Complexity