2204 - New Approaches to Understanding and Addressing Inequality

Session Submission Type: Paper Session 100min

Description

Understanding the forms, causes and consequences of social inequality has been a central focus of sociology since the discipline’s inception. Decades of increasing economic and political polarization continue to underscore the high intellectual and practical stakes of continuing this project. In recent years, scholars have responded by drawing on an ever increasing methodological and conceptual toolkit to advance the ways we approach this task— e.g. the deployment of computational methodologies for analyzing “big data” sets, the growth of large scale multi-site fieldwork studies, the development of new forms of experiments and simulations, the application novel evidence based policy interventions, the renewed interest in interdisciplinary collaboration, and the development of new concepts and theoretical models. This session will feature the cutting-edge work being conducted by sociologists as they apply new approaches to sociology’s longstanding, but always urgent charge: understanding and addressing inequality.

Sub Unit

• Section on Inequality, Poverty, and Mobility / New Approaches to Understanding and Addressing Inequality

Session Organizer

• Corey M. Abramson, University of Arizona

Presider

• Corey M. Abramson, University of Arizona

Individual Presentations

• Intersectional Inequality: A Fuzzy-Set Analysis of Family Background, Test Scores, and Poverty - Charles C. Ragin, University of California, Irvine; Peer C. Fiss, University of Southern California

• Flows and Boundaries: A Network Framework for Understanding Occupational Mobility in the Labor Market - Barum Park; Siwei Cheng, New York University

• Estimating Heterogeneity in Sociological Effects: From Interactions to Machine Learning - Jennie E. Brand, University of California - Los Angeles; Jiahui Xu, University of California-Los Angeles; Bernard Koch, University of California, Los Angeles; Pablo Geraldo, University of California-Los Angeles

• Assessing Income Inequality beyond Aggregate Measures - Tim Futing Liao, University of Illinois

• Exploring the Use of Machine Vision to Understand Neighborhood Inequality - Laura K. Nelson, Northeastern University; Jeffrey L. Sternberg, Northeastern University; Tirthak Lalitbhai Patel, Northeastern University; Devesh Tiwari, Northeastern University