Place and Punishment: The Spatial Context of Mass Incarceration

Original Paper



Research on race and urban poverty views incarceration as a new and important aspect of social disadvantage in inner-city neighborhoods. However, in quantitative studies of the spatial distribution of imprisonment across neighborhoods, the pattern outside urban areas has not been examined. This paper offers a unique analysis of disaggregated prison admissions and investigates the spatial concentrations and levels of admissions for the entire state of Massachusetts.


Spatial regressions estimate census tract-level prison admission rates in relation to racial demographics, social and economic disadvantage, arrest rates, and violent crime; an analysis of outlier neighborhoods examines the surprisingly high admission rates in small cities.


Regression analysis yields three findings. First, incarceration is highly spatially concentrated: census tracts covering 15% of the state’s population account for half of all prison admissions. Second, across urban and non-urban areas, incarceration is strongly related to concentrated disadvantage and the share of the black population, even after controlling for arrest and crime rates. Third, the analysis shows admission rates in small urban satellite cities and suburbs comprise the highest rates in the sample and far exceed model predictions.


Mass incarceration emerged not just to manage distinctively urban social problems but was characteristic of a broader mode of governance evident in communities often far-removed from deep inner-city poverty. These notably high levels and concentrations in small cities should be accounted for when developing theories of concentrated disadvantage or policies designed to ameliorate the impacts of mass incarceration on communities.


Incarceration Neighborhoods Race and ethnicity Poverty Spatial regression 


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of SociologyBoston UniversityBostonUSA

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