In this article, we describe how residential segregation and individual racial disparities generate racialized patterns of subprime lending and lead to financial loss among black borrowers in segregated cities. We conceptualize race as a cumulative disadvantage because of its direct and indirect effects on socioeconomic status at the individual and neighborhood levels, with consequences that reverberate across a borrower's life and between generations. Using Baltimore, Maryland as a case study setting, we combine data from reports filed under the Home Mortgage Disclosure Act with additional loan-level data from mortgage-backed securities. We find that race and neighborhood racial segregation are critical factors explaining black disadvantage across successive stages in the process of lending and foreclosure, controlling for differences in borrower credit scores, income, occupancy status, and loan-to-value ratios. We analyze the cumulative cost of predatory lending to black borrowers in terms of reduced disposable income and lost wealth. We find the cost to be substantial. Black borrowers paid an estimated additional 5 to 11 percent in monthly payments and those that completed foreclosure in the sample lost an excess of $2 million in home equity. These costs were magnified in mostly black neighborhoods and in turn heavily concentrated in communities of color. By elucidating the mechanisms that link black segregation to discrimination we demonstrate how processes of cumulative disadvantage continue to undermine black socioeconomic status in the United States today.

Recent studies have used statistical methods to show that minorities were more likely than equally qualified whites to receive high-cost, high-risk loans during the U.S. housing boom, evidence taken to suggest widespread discrimination in the mortgage lending industry. The evidence, however, was indirect, being inferred from racial differentials that persisted after controlling for other factors known to affect the terms of lending. Here we assemble a qualitative database to generate direct evidence of discrimination. Using a sample of 220 statements randomly selected from documents assembled in the course of recent fair lending lawsuits, we code texts for evidence of individual discrimination, structural discrimination, and potential discrimination in mortgage lending practices. We find that 76 percent of the texts indicated the existence of structural discrimination, with only 11 percent suggesting individual discrimination alone. We then present a sample of texts that were coded as discriminatory to reveal the way in which racial discrimination was embedded within the social structure of U.S. mortgage lending, and to reveal the specific microsocial mechanisms by which this discrimination was effected.

In the decade leading up to the U.S. housing crisis, black and Latino borrowers disproportionately received high-cost, high-risk mortgages—a lending disparity well documented by prior quantitative studies. We analyze qualitative data from actors in the lending industry to identify the social structure though which this mortgage discrimination took place. Our data consist of 220 depositions, declarations, and related exhibits submitted by borrowers, loan originators, investment banks, and others in fair lending cases. Our analyses reveal specific mechanisms through which loan originators identified and gained the trust of black and Latino borrowers in order to place them into higher-cost, higher-risk loans than similarly situated white borrowers. Loan originators sought out lists of individuals already borrowing money to buy consumer goods in predominantly black and Latino neighborhoods to find potential borrowers, and exploited intermediaries within local social networks, such as community or religious leaders, to gain those borrowers’ trust.

This paper offers a mixed-method analysis of the municipal-level consequences of an affordable housing development built in suburban New Jersey. Opponents of affordable housing development often suggest that creating affordable housing will harm surrounding communities. Feared consequences include increases in crime, declining property values, and rising taxes. To evaluate these claims, the paper uses the case of Mt. Laurel, NJ – the site of a landmark affordable housing legal case and subsequent affordable housing development. Employing a multiple time series group control design, we compare crime rates, property values, and property taxes in Mt. Laurel to outcomes in similar nearby municipalities that do not contain comparable affordable housing developments. We find that the opening of the affordable housing development was not associated with trends in crime, property values, or taxes, and discuss management practices and design features that may have mitigated potential negative externalities.

WellWatch was a webtool designed to create a collaborative space for communities and academics to monitor, study, and respond more effectively to the emerging shale gas industry. This article reflects on the successes and failures of the first iteration of WellWatch for academic research and its community of nonacademic participants. For academics, this tool succeeded in gathering rich narratives of the personal experiences of people living amidst natural gas development. These narratives, from multiple locations, provide insight into structural patterns associated with this industry. They gave a lens into social processes emerging from and responding to these structures. Taken together, these narratives help define next steps for research. WellWatch also proved useful for non-academics, primarily impacted landowners from Colorado and Pennsylvania. It helped landowners manage problems of individual isolation by networking them with other landowners and providing useful information about how to manage and resolve problems. It also furnished data to the people affected that they could use in their own advocacy, with potentially important effects. The tool also helped non-profit advocacy groups in assisting with networking and with sharing best practices. Based on this review of WellWatch, the article proposes a method for further developing collaborative ethnographic and community-based research through networked digital media.Key words: citizen science, community based participatory research, digital ethnography, hydraulic fracturing para-ethnography, multi-sited ethnography