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How Collectivists and Interdependent Communities React to Adverse Events

Delia Baldassarri, New York University

Year selected for award: 2024

Social Cohesion in Action: How Collectivists and Interdependent Communities React to Adverse Events

Principal Investigator: Delia Baldassarri, New York University

Co-Principal Investigators: Maria Abascal (New York University), Christopher Barrie (New York University), Byungkyu Lee (New York University), Joshua Tucker (New York University), and Jonathan Nagler (New York University)

Years of Award: 2024-2029

Managing Service Agency: Army Research Office

Project Description:
We study social cohesion in action, exploring how individuals, groups, and communities react to sudden adversity, such as infrastructure failures, natural disasters, mass shootings, political conflicts, and health emergencies. Social cohesion is widely seen as crucial in managing crises, but existing research lacks insight into how different models of cohesion shape local and global responses. We argue that the traditional collectivist model, based on shared identity in homogeneous communities, struggles in increasingly complex, diverse societies. Instead, we advance a model of social cohesion based on interdependence and generalized pro-sociality, where trust and cooperation grow across group boundaries through differentiation and economic interdependence.

The project has three interconnected modules and integrates computational tools, digital trace data, and conventional methods like surveys and field experiments to capture real-time community responses and assess the effects of adversity on social cohesion globally. Module 1 conceptualizes and measures the building blocks of the collectivist and interdependent models of social cohesion, testing them against prosocial behavior using a large-scale, cross-national experimental design. Module 2 explores how communities respond to adverse events by analyzing data from civic apps, supported by interviews and qualitative text analysis. Module 3 uses language models to scale up natural experimental designs for understanding the effects of adverse events on social cohesion and trust cross-nationally.