SBIR-STTR Award

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. PROPOSED COMMERCIAL APPLICATIONS: 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.

Ethnic residential segregation is an enduring feature of American cities. Residential location and neighborhood context are important factors that affect the life chances of individuals, families, and minorities. Two problems hinder general understanding of segregation patterns and the forces that shape them. First, the research literature relies on technical, quantitative indices computed from specialized data sets to document segregation patterns and trends. Second, conventional methodologies for exploring effects of hypothesized determinants of segregation (market forces, the spatial and demographic organization of cities, household preferences, constraints imposed by discrimination, etc.) require advanced data analysis skills. To overcome these problems Mark Fossett of Texas A&M University authored SimSeg, a computer program that uses intuitive graphical presentations to help students comprehend segregation patterns and simulation capabilities to help researchers explore different theories about the determinants of segregation patterns. In Phase II, Amber Waves Software and Texas A&M will refine and extend the SimSeg model by: 1) improving its ability to represent the spatial and demographic structure of American cities, 2) enhancing its model of household residential choices, 3) enabling the model to represent any set of ethnic groups, 4) developing tools that will enable students, researchers, and social science professionals to build their own simulation scenarios, 5) working with outside sociologists to ensure the scientific merits of the SimSeg model, and 6) conducting extensive internal verification and external validation exercises. Additionally, Amber Waves Software and Texas A&M will build a library of simulation scenarios based on real cities and develop extensive technical documentation of the SimSeg model.

Thesaurus Terms:
computer program /software, computer simulation, educational resource design /development, geographic difference, housing, human population dynamics, social integration computer graphics /printing, computer system design /evaluation, prejudice, socioeconomics behavioral /social science research tag