Ethnic residential segregation is an enduring feature of American cities. Residential location and neighborhood context are important results that affect the life chances of individuals, families, and groups. Ethnic segregation is widely studied in college courses focusing on minority groups, poverty, social problems, and urban areas. Two problems hinder undergraduate students' ability to understand segregation patterns and the forces that shape them. First, the research literature relies on technical, quantitative indices computed from specialized data sets to document patterns and trends in segregation. Second, conventional methodologies for exploring effects of hypothesized determinants of segregation (e.g., market forces, the spatial- demographic organization of cities, household preferences, constraints imposed by discrimination, etc.) require data analysis skills that undergraduate students do not have. To overcome these problems Mark Fossett of Texas A&M University authored SimSeg, a computer program that uses graphical presentations to help students comprehend segregation patterns and simulation capabilities to help students explore different theories about the determinants of segregation patterns. In Phase I, Amber Waves Software (AWS) will produce a beta prototype of SimSeg for the educational market In Phase II, AWS and Texas A&M will refine and extend the program and bring it to commercial distribution.
The resulting software will have commercial application as a teaching tool for college undergraduate courses in the social sciences focusing on urban areas, social problems, and minority groups.
| Fossett, Mark (2011) Generative Models of Segregation: Investigating Model-Generated Patterns of Residential Segregation by Ethnicity and Socioeconomic Status. J Math Sociol 35:114-145 |
