The Growth, Scope, and Spatial Distribution of People With Felony Records in the United States, 1948–2010

Abstract

The steep rise in U.S. criminal punishment in recent decades has spurred scholarship on the collateral consequences of imprisonment for individuals, families, and communities. Several excellent studies have estimated the number of people who have been incarcerated and the collateral consequences they face, but far less is known about the size and scope of the total U.S. population with felony convictions beyond prison walls, including those who serve their sentences on probation or in jail. This article develops state-level estimates based on demographic life tables and extends previous national estimates of the number of people with felony convictions to 2010. We estimate that 3 % of the total U.S. adult population and 15 % of the African American adult male population has ever been to prison; people with felony convictions account for 8 % of all adults and 33 % of the African American adult male population. We discuss the far-reaching consequences of the spatial concentration and immense growth of these groups since 1980.

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Notes

  1. 1.

    The terms felon and prisoner refer to conviction and incarceration status rather than criminal behavior. These estimates are thus a reflection of a rising punishment rate, even as crime rates have declined (see, e.g., Uggen and McElrath 2013). Our estimates by race should not be interpreted as measures of differential rates of criminal behavior by race but rather as differential rates of punishment by race. Racial disparities in punishment rates result not merely from criminal behavior but also from discriminatory treatment within the criminal justice system, as others have shown (see, e.g., Western 2006).

  2. 2.

    We do not present estimates for changes in Hispanic ethnicity because less historical demographic information is available on the ethnicity of people in prison or under felony supervision (for 2010 rates, see Shannon and Uggen 2013).

  3. 3.

    Because we use de-identified aggregate data, factors such as aliases are unlikely to significantly affect our estimates. State releasee information is based on a simple count of the number of people leaving supervision, without regard to individual releasees’ names or identities. Our estimates thus model death and recidivism for the total release cohort rather than tracking individuals who may have multiple names or records within the system.

  4. 4.

    A recent report from the Bureau of Justice Statistics using data on prisoners released in 2005 in 30 states found a 17.5 % reincarceration rate at 1 year, 28.8 % at 2 years, and 36.2 % at 3 years (Durose et al. 2014). We apply the slightly higher rate from previous studies so that our estimates are more conservative.

  5. 5.

    Little is known about how mobility patterns of this population might differ from the population as a whole. Available evidence suggests that at least 95 % of former prison inmates remain in the same state postrelease (LaVigne and Kachnowski 2003; LaVigne and Mamalian 2003; LaVigne and Thomson 2003; Watson et al. 2004). Given that this population faces significant socioeconomic challenges as a result of criminal conviction (see, e.g., Wakefield and Uggen 2010), there is little reason to believe that people with felony records are more mobile than the general population. If they are less mobile than the population as a whole, our estimates will remain conservative.

  6. 6.

    After calculating mobility-adjusted estimates for each state and year, we found that the resulting national totals for both populations were inflated by 2 % over national totals without mobility adjustments because we add in mobility gains each year and reduce those gains for recidivism and mortality but not subsequent mobility losses. To compensate for this inflation, we adjust each state’s estimate by a factor of 0.98 in each year. This is a reasonable assumption because 2 % to 3 % of the U.S. population moved from one state to another annually from 1980 to 2010, with the percentage declining just below 2 % in more recent years (U.S. Census Bureau 2013).

  7. 7.

    Integral to this calculation is the specification of a spatial weights matrix in order to explicitly account for the spatial arrangement of the data. This specification determines the “neighborhood” for each observation. Weights matrices can be determined based on distance (e.g., from one state centroid to another) or by contiguity (shared borders). Contiguity matrices can be established at higher or lower orders (e.g., first, second, third) and vary in the neighbors included (e.g., rook, queen). For example, a first-order queen contiguity matrix takes into account adjacent neighbors in all directions at the first level out from the state in question.

  8. 8.

    We also tested these results excluding states with especially high rates (e.g., California and Florida) as well as states with less than 10,000 African Americans in the total population; our findings were similar.

  9. 9.

    We caution against a direct comparison between our article and Muller and Wildeman’s (2016) because of differences in methods and the outcome of interest. Muller and Wildeman (2016) used point-in-time projection, and our analysis uses release cohorts over a much longer period. As Muller and Wildeman (2016:1505) noted, these methodological differences hinder drawing direct comparisons between the two types of analyses. In addition, Muller and Wildeman estimated risk of incarceration only, whereas we estimate felony convictions with or without a sentence of incarceration.

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Acknowledgments

The authors thank Rochelle Schmidt, Maria Kamenska, and Suzy McElrath for invaluable research assistance and support.

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Correspondence to Sarah K. S. Shannon.

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Shannon, S.K.S., Uggen, C., Schnittker, J. et al. The Growth, Scope, and Spatial Distribution of People With Felony Records in the United States, 1948–2010. Demography 54, 1795–1818 (2017). https://doi.org/10.1007/s13524-017-0611-1

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Keywords

  • Incarceration
  • Felony conviction
  • Punishment
  • Inequality