I am a PhD Post Doc at the University of Washington’s eScience Institute and department of Sociology researching the intersection of residential segregation, neighborhood change, and housing inequality. I use data analytics to examine evictions, micro-segregation trends, and the effects of gentrification on low-income households.
In addition to my academic research agenda, I am committed to designing and conducting policy-relevant research and developing academic relationships with local government, stakeholders, and advocates to help answer difficult sociological and demographic questions.
Race, Market, and Neighborhood Dynamics of Evictions
Timothy A. Thomas (dissertation)
While research on evictions has focused primarily on household-level dynamics, there has not been an extensive ecological evaluation on the broader metropolitan and neighborhood-level effects that contribute to the geographic concentration of evictions. This dissertation bridges that gap by analyzing neighborhood ethno-racial compositions, socioeconomics, and housing market dynamics related to evictions in King County, WA. Results show that neighborhood racial diversity, higher poverty, affordable housing, and market demand predict higher rates of evictions. Nearby neighborhood effects, such as low- rent and low-poverty, has a large impact on local eviction rates. Furthermore, neighborhoods that saw increases in Black and Latino populations and declines in education and new movers over time also see higher rates of eviction. This study highlights how place-based racial and economic inequality is shaped by the history of the political economy of the region, segregation, and housing exclusion that produced the contemporary eviction concentrations we see today.
Segregation within Integration:
Exploring Micro-Level Segregation in Seattle’s Integrated Tracts Using Spatial and Qualitative Analysis
Timothy A. Thomas & Ryan Gabriel
Residential segregation has decreased in recent decades, leading to a rise in the number of integrated neighborhoods. However, pockets of segregation may still exist within these diverse areas. Using a mixed-methods approach, we investigate whether integrated neighborhoods show substantive levels of micro-segregation through physical and social buffers created by topography, the built environment, economic structures, and racial history. Utilizing block-level spatial demographic analysis of three of Seattle’s integrated tracts, we find definitive micro-segregation coinciding with social, commercial, and topographic buffers––potentially impeding interaction between racial groups. We also find that contemporary segregative patterning of racial groups within these areas is associated with historical neighborhood formation and segregation. Our research has implications for studies of residential segregation, how it is measured, and highlights the impacts of historical policies and neighborhood change on residential diversity.
Measures of Human Mobility Using Mobile Phone Records Enhanced with GIS Data
Nathalie E. Williams, Timothy A. Thomas, Matthew Dunbar, Nathan Eagle, & Adrian Dobra
In the past decade, large scale mobile phone data have become available for the study of human movement patterns. These data hold an immense promise for understanding human behavior on a vast scale, and with a precision and accuracy never before possible with censuses, surveys or other existing data collection techniques. There is already a significant body of literature that has made key inroads into understanding human mobility using this exciting new data source, and there have been several different measures of mobility used. However, existing mobile phone based mobility measures are inconsistent, inaccurate, and confounded with social characteristics of local context. New measures would best be developed immediately as they will influence future studies of mobility using mobile phone data. In this article, we do exactly this. We discuss problems with existing mobile phone based measures of mobility and describe new methods for measuring mobility that address these concerns. Our measures of mobility, which incorporate both mobile phone records and detailed GIS data, are designed to address the spatial nature of human mobility, to remain independent of social characteristics of context, and to be comparable across geographic regions and time. We also contribute a discussion of the variety of uses for these new measures in developing a better understanding of how human mobility influences micro-level human behaviors and well-being, and macro-level social organization and change.
Rwanda gridded mobility measures