One of the most important criminal legal system disparities has long been difficult to decipher: Which communities throughout the state do incarcerated people come from? Anyone who lives in or works within heavily policed and incarcerated communities intuitively knows that certain neighborhoods disproportionately experience incarceration. But data have rarely been available to quantify how many people from each community are imprisoned with any real precision.1
But now, thanks to a redistricting reform that ensures incarcerated people are counted correctly in the legislative districts they come from, we can understand the geography of incarceration in Maryland with up-to-date data. Maryland is one of over a dozen states that have ended prison gerrymandering, and now count incarcerated people where they legally reside — at their home address — rather than in remote prison cells for redistricting purposes. This type of reform, as we often discuss, is crucial for ending the siphoning of political power from disproportionately Black and Latino communities to pad out the mostly rural, predominantly white regions where prisons are located. And when reforms like Maryland’s are implemented, they bring along a convenient side effect: In order to correctly represent each community’s population counts, states must collect detailed state-wide data on where imprisoned people call home, which is otherwise impossible to access.
Using this redistricting data, we found that in Maryland, incarcerated people come from all over the state, but are disproportionately from Baltimore City. Looking at local data, we also find that some areas of the state — like the southern Eastern Shore and Hagerstown — are also disproportionately affected by incarceration. While Maryland incarcerates a smaller share of its residents than all but 13 U.S. states, examining these data by county, city, and even neighborhood reveals surprising and troubling patterns of high incarceration in both specific communities within Baltimore and also the smaller and historically under-resourced Eastern Shore communities.
In addition to helping policy makers and advocates effectively bring reentry and diversion resources to these communities, this data has far-reaching implications. Around the country, high imprisonment rates are correlated with other community problems related to poverty, employment, education, and health. Researchers, scholars, advocates, and politicians can use the data in this report to advocate for bringing more resources to their communities.
Most broadly, we find that people in Maryland prisons come from every corner of the state. Every single county in the state — and every state legislative district — is missing a portion of its population to incarceration in state prison. The idea that incarceration is a problem uniquely experienced in cities is a myth. While it is true that Baltimore has a disproportionately high incarceration rate, residence data shows it is not alone in this regard. A number of less populous areas, including Wicomico, Dorchester, and Somerset counties on the Eastern Shore,3 rank in the top fifth of Maryland counties when it comes to prison incarceration rates with over 570 people in state prison for every 100,000 county residents. Compared to the state-wide incarceration rate of 193 people for every 100,000 residents, these three Eastern Shore counties are losing relatively large portions of their populations to state prisons.4
While incarceration affects every part of the state, it tends to be concentrated in a relatively small number of geographic areas. For example, while 9% of Maryland residents call Baltimore home, 40% of Maryland residents in state prison are from the city. By contrast, the most populous county in the state — Montgomery County — is home to 17% of Maryland residents, but only 4% of the state prison hails from this county.
Despite their geographic proximity, these two neighborhoods in Baltimore experience vastly different rates of incarceration: people in Southwest Baltimore are 8 times more likely to be imprisoned than residents of Midtown.
Even within communities, the data show dramatic and troubling differences in incarceration rates between neighborhoods. Over one third of people in state prison from Baltimore City hail from just ten of the city’s 55 neighborhoods.5 The neighborhood of Midtown had an incarceration rate of 262 people in state prison per 100,000 neighborhood residents, while Southwest Baltimore had an incarceration rate eight times higher at 2,223 people in state prison per 100,000 residents.
While all communities are missing some of their members to imprisonment, in places where large numbers of adults — parents, workers, voters — are locked up, incarceration has a broader community impact. The large number of adults drained from a relatively small number of geographical areas seriously impacts the health and stability of the families and communities left behind.6
We already know that communities with high incarceration rates simultaneously tend to face other negative outcomes. In our analysis of the previous decade’s data on where incarcerated people in Maryland are from, we found that Baltimore communities with high rates of incarceration were more likely to have high unemployment rates, long average commute times, low household income, a high percentage of residents with less than a high school diploma or GED, decreased life expectancy, high rates of vacant or abandoned properties, and higher rates of children with elevated blood-lead levels, compared to neighborhoods less impacted by incarceration.
JPI plans to produce a report in late 2022 that will present a deeper dive on these and other social indicators using Maryland data. National research has revealed similar correlations7 in communities around the country:
Maryland residents can use the data in this report to examine granular local-level and state-wide correlations and choose to allocate needed resources to places hardest hit by incarceration.
The 9 data tables provided here have great potential for community advocacy and future research.
First and most obviously, these data can be used to determine the best locations for community-based diversion programs that help prevent involvement with the criminal legal system, such as offices of neighborhood safety and mental health response teams located outside of police departments. The data can also help guide reentry services (which are typically provided by nonprofit community organizations) to areas of Maryland that need them most.
But even beyond the obvious need for diversion and reentry services, our findings also point to geographic areas that deserve greater investment in programs and services that indirectly prevent criminal legal involvement or mitigate the harm of incarceration. After all, decades of research show that imprisonment leads to cascading collateral consequences, both for individuals and their loved ones. When large numbers of people disappear from a community, their absences are felt in countless ways. They leave behind loved ones, including children, who experience trauma, emotional distress, and financial strain. Simultaneously, the large numbers of people returning to these communities (since the vast majority of incarcerated people who are incarcerated do return home) face a host of reentry challenges and collateral consequences resulting from their incarceration, including difficulty finding employment and a lack of housing. People impacted by the justice system tend to have extremely diminished wealth accumulation. And those returning from prison and jail may carry back to their communities PTSD and other mental health issues from the trauma they’ve experienced and witnessed behind bars.
And since we know place of origin correlates with so many other metrics of wellbeing, we can and should target these communities for support and resources beyond what we typically think of as interventions to prevent criminal legal system contact. In communities where the state or city has heavily invested in policing and incarceration (i.e. the high-incarceration neighborhoods we find in our analysis), our findings suggest that those resources would be better put toward reducing poverty and improving local health, education, and employment opportunities.
For example, we know that large numbers of children in high incarceration areas may be growing up with the trauma and lost resources that come along with having an incarcerated parent, and that these children are also more likely to experience incarceration. The information in this report can help with planning and targeting supports, resources, and programming designed to not only respond to the harms caused by incarceration, but disrupt the cycle of familial incarceration.
We invite community organizers, service providers, policymakers, and researchers to use the data tables made available in this report to make further connections between mass incarceration and various outcomes, to better understand the impact of incarceration on their communities.
This report capitalizes on the unique opportunity presented by Maryland’s ending of prison gerrymandering, which allows us to determine accurately where people incarcerated in state prisons come from. In this report’s linked datasets, we aggregate this data by a number of useful state-wide geographies such as counties, legislative districts, and cities, and for some areas such as Baltimore neighborhoods and Montgomery County neighborhoods.
This section of the report discusses how we processed the data, some important context and limitations on that data, and some additional context about the geographies we have chosen to include in this report and appendices.. The goal of this report is not to have the final word on the geographic concentration of incarceration, but to empower researchers and advocates — both inside and outside of the field of criminal justice research — to use our dataset for their own purposes. For example, if you are an expert on a particular kind of social disadvantage and have some data organized by county, zip code, legislative district, or other breakdown and want to add imprisonment data to your dataset, we probably have exactly what you need in a prepared appendix described below.
This report and its data are one in a series of similar reports we are releasing in the spring and summer of 2022, focusing on 13 states — California, Colorado, Connecticut, Delaware, Maryland, Montana, Nevada, New Jersey, New York, Pennsylvania, Rhode Island, Virginia, and Washington — which counted incarcerated people at home for redistricting purposes, and therefore also made this analysis possible. This report can also be seen as a template for other states because while not all states have ended prison gerrymandering, most state departments of corrections already have near-complete home residence records in an electronic format. States that have not yet ended prison gerrymandering should be encouraged to continue improving their data collection, and to share the data (under appropriate privacy protections) so that similar analyses could be performed.
Maryland’s law ending prison gerrymandering required the Maryland Department of Public Safety and Correctional Services to share the home addresses of people in state prisons on Census Day 2020 with redistricting officials, so that these officials could remove imprisoned people from the redistricting populations reported by the Census for the facilities’ locations and properly credit people to their home communities. The adjusted data was then made available for state and local officials to use to draw new legislative boundaries. As a side effect, this groundbreaking dataset allows researchers to talk in detail for the first time about where incarcerated people came from.
Creating the tables in this report required several steps which were expertly performed by Peter Horton at Redistricting Data Hub:
Our analysis in this report documents the home addresses of 15,242 people in Maryland state prisons, which is somewhat less than the state’s total prison population of 19,802 on Census day. These numbers are different for a variety of reasons, including policy choices made when the legislation ending prison gerrymandering was created and others are just the practical outcome of valiant state efforts to improve federal census data, or the process of repurposing that dataset for this entirely different project.
From the perspective of improving democracy in Maryland, the state’s reallocation efforts were a success, reducing both the unearned enhancement of political representation in prison-hosting areas and reducing the dilution of representation in the highest-incarceration districts. From the perspective of using that data to discuss the concentration of incarceration, some readers may want to be aware of some the reasons why our report discusses the home addresses of 15,242 people when they may be aware that the state prison system had 19,802 people on Census day:
Similarly, this report doesn’t reflect the other groups of people incarcerated from particular communities who are not reflected in these data,14 because they were:
We’ve organized the data in this report around several popular geographies, as defined by the federal government, by the state, or by individual cities, with the idea that the reader can link our data to the wealth of existing social indicator data already available from other sources.
Unfortunately, the reader may desire data for a specific geography that we have not made available — for example, their own neighborhood, as they conceive of its boundaries. Often, there was not a readily accessible and official map that we could use that defined that boundary; so where the reader has this need, we urge the reader to look for other geographies in our datasets that can be easily adapted to their needs, either one that is similar enough to their preferred geography or by aggregating several smaller geographies together to match your preferred geography.
We also want to caution subsequent users of this data that some geographies change frequently and others change rarely, so they should note the vintage of the maps we used to produce each table. For example, county boundaries change very rarely, and when they do, it is often in extremely small ways. On the other hand, legislative districts may change frequently and significantly, so depending on your goals some specific tables may be more or less applicable for your future use.
Finally, readers should note that occasionally the incarcerated numbers in our tables for some geographies will not sum precisely to the total 15,242 home addresses used in this report. That discrepancy arises because of how census blocks - the basic building block of legislative districts - nest or fail to nest within geographies drawn by agencies other than the Census Bureau.
Criminal legal system data is often poorly tracked, meaning researchers must cobble together information from different sources. But by using complete data from state redistricting committees, this report (and a series of other state reports that the Prison Policy Initiative developed with state partners ) are uniquely comprehensive and up-to-date. The series includes two previous reports on Maryland (published in 2015, in collaboration with the Justice Policy Institute) and New York (published in 2020, in collaboration with VOCAL-NY), and our newest report(s) on California, Colorado, Connecticut, Delaware, Montana, Nevada, New Jersey, New York, Pennsylvania, Virginia, and Washington.
While these reports are the first to use redistricting data to provide detailed, local-level data on where incarcerated people come from statewide, other organizations have previously published reports that focused on individual cities or that provided data across fewer types of geographic areas. For example, the Justice Mapping Center had a project that showed residence data for people admitted to or released from state prisons in a given year for almost two dozen states. That project made those states’ annual admission and release data available at the zip code and census tract levels, most recently mapping 2008-2010 data. Separately, it also mapped the residences of people admitted to state prisons from New York City down to the block level using 2009 data.
Another resource (particularly helpful for states that are not included in our series of reports) is Vera Institute for Justice’s Incarceration Trends project, which maps prison incarceration rates for 40 states at the county level, based on county of commitment (meaning where individuals were convicted and committed to serve a sentence, which is often but not necessarily where they lived). ↩
The Baltimore Data Collaborative and the Baltimore City Department of Planning divided Baltimore into 55 Community Statistical Areas (CSAs). These 55 units combine Census Bureau geographies together in ways that match Baltimore’s understanding of community boundaries, and are used in social planning. For the purposes of this report, we are using CSAs to analyze imprisonment data at the neighborhood level. ↩
This area of the Eastern Shore is primarily rural and agricultural. According to Census 2020 data, there is a significant population of Black residents in these counties, and there is also likely to be a significant population of seasonal workers. For example, Somerset County’s population is 39% Black, while only 30% of Maryland’s statewide population is Black. ↩
As explained in the methodology, this report’s incarceration rate is based on the number of people in state prison who were reallocated to individual communities as part of the state’s law ending prison gerrymandering. This number is necessary for making apples-to-apples comparisons of incarceration between specific communities and the state as a whole. For the purposes of comparing incarceration in Maryland with that of other states, other more common metrics would be more useful. For these other uses, we would recommend using other numbers for the statewide incarceration rate, likely either the 258 per 100,000 published by the Bureau of Justice Statistics in Prisoners in 2020 for the number of people in state prison per 100,000 residents, or our more holistic number of 531 per 100,000 residents used in States of Incarceration: The Global Context 2021 that includes people in state prisons, federal prisons, local jails, youth confinement, and all other forms of incarceration. ↩
For the purposes of this analysis of city-wide trends by neighborhood, we used Community Statistical Areas (CSAs), described in footnote 2, to approximate neighborhoods. The CSAs solve a difficult problem for people who study communities: neighborhoods are fluid, and statistical data is often collected in ways that are incompatible with shifting or ill-defined boundaries. For example, the City of Baltimore has over 270 neighborhoods, but the boundaries of those neighborhoods do not necessarily match the Census Bureau’s community boundaries and have a wide range of populations, making it hard to accurately analyze and compare these geographies. For these reasons, throughout this report, we are using the 55 Baltimore Community Statistical Areas to approximate neighborhoods. ↩
These impacts of incarceration on families and communities include higher rates of disease and infant mortality, housing instability, and financial burdens related to having an incarcerated loved one. For more detailed information on how incarceration impacts families and communities, see On life support: Public health in the age of mass incarceration from the Vera Institute of Justice. ↩
These various correlative findings are once again in line with previous research on health disparities across communities, which have been linked to neighborhood factors such as income inequality, exposure to violence, and environmental hazards that disproportionately affect communities of color. Public health experts consider community-level factors such as these — including incarceration — “social determinants of health.” To counteract these problems, they suggest taking a broad approach, addressing the “upstream” economic and social disparities through policy reforms, as well as by increasing access to services and supports, such as improving access to clinical health care. ↩
Asthma prevalence has been used as a tool to measure population health in both sociological and public health research because it is easily correlated with environmental factors like air quality and triggers (i.e. second hand smoke, mold, dust, cockroaches, dust mites), as well as access to appropriate healthcare and healthcare literacy. See the American Lung Association’s Public Policy Position for a literature review of the relevant public health research. ↩
Again, this finding is consistent with previous research on the relationship between education and imprisonment rates. We previously reported that the high school educations of over half of all formerly incarcerated people were cut short. This is in line with earlier studies showing that people in prison have markedly lower educational attainment, literacy, and numeracy than the general public, and are more likely to have learning disabilities. We also know there are relationships between parental incarceration and educational performance. ↩
People in prison remain residents of their home districts, but at redistricting time, they are assigned to the district where they are incarcerated. This skewed population assignment means that the more people in prison that are counted in a district, the fewer actual constituents the prison district legislator has, but is still allowed a full vote in the General Assembly. Therefore, people who live near prisons each get a stronger say in state government than people who live in a district without any of these “phantom constituents.” ↩
Fletcher v. Lamone, 831 F. Supp. 2d 887, 897 (D. Md. 2011), aff’d, 567 U.S. 930 (2012). ↩
This list of groups of people who could not be counted at home is yet another set of reasons why the U.S. Census Bureau is the ideal agency to end prison gerrymandering: they are the only party with the ability to provide a complete solution and they can do this work far more efficiently than the states can. ↩
We would like to thank the Redistricting Data Hub, particularly Peter Horton, for providing valuable technical expertise and the key data in the appendix tables. Redistricting Data Hub’s assistance processing the redistricting data and connecting us with other demographic data enabled us to produce and distribute these reports faster and more affordably than would otherwise have been possible.
Founded in 1997, the Justice Policy Institute (JPI) is a nonprofit organization developing workable solutions to problems plaguing the juvenile and criminal legal systems. JPI envisions a society with safe, equitable, and healthy communities; just and effective solutions to social problems; and the use of incarceration only as a last resort. For over 20 years, JPI has been engaged in criminal legal reform efforts in Maryland, generating over two dozen publications on Maryland’s correctional challenges.
The non-profit, non-partisan Prison Policy Initiative produces cutting-edge research that exposes the broader harm of mass criminalization and sparks advocacy campaigns that create a more just society. In 2002, the organization launched the national movement against prison gerrymandering when it showed that the way the Census Bureau counts incarcerated people — as residents of a prison cell, instead of at their homes — distorts our democracy and dilutes the voices of people who do not live near prisons. Since then, over a dozen states, including Maryland, have used Prison Policy Initiative’s research to end prison gerrymandering. Roughly half of the country now lives in a place that has formally rejected prison gerrymandering.