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Where people in prison come from:
The geography of mass incarceration in New Jersey

by Emily Widra, Henal Patel, and Ronald Pierce   Tweet this
June 2022
Press release

One of the most important criminal legal system disparities in New Jersey has long been difficult to decipher: Which communities 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 never been available to quantify with any real precision how many people from each community are imprisoned.¹

But now, thanks to redistricting reform that ensures incarcerated people are counted correctly in the legislative districts they come from, we can understand the geography of incarceration in New Jersey. New Jersey 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. 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 New Jersey’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 New Jersey incarcerated people come from all over the state, but are disproportionately from a few specific cities, most notably Camden, Atlantic City, Paterson, Newark, and Jersey City. A deeper dive into the data shows that even within these cities there are dramatic differences in rates of incarceration between neighborhoods, often along racial and socioeconomic lines. Finally, the data shows that even in a state like New Jersey, with a predominantly urban population, many rural counties (including Cumberland, Salem, and Cape May counties) are disproportionately affected by incarceration.

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 elected officials can use the data in this report to advocate for bringing more resources to their communities.

Incarcerated people come from all over New Jersey — but disproportionately from some places more than others

County trends

Most broadly, we find that people in New Jersey 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 the counties that contain urban or more densely populated areas — like Essex County (Newark) and Camden County (Camden)³ — tend to have disproportionately high imprisonment rates, residence data shows that some of the counties with smaller populations have disproportionately high imprisonment rates as well.

Importantly, ending prison gerrymandering in New Jersey had a notable impact on the population demographics of Essex County. The net population of Essex County decreased after the census data was adjusted to reflect incarcerated people being counted in their home addresses, because people incarcerated there were allocated elsewhere. However, the Black population in Essex County actually increased, as Black people from Essex who were incarcerated elsewhere were reallocated back to Essex.

A number of less populous counties, including Cumberland, Cape May, and Salem counties in southern New Jersey,⁴ all have higher imprisonment rates than the state as a whole (state-wide imprisonment rate is 170 people for every 100,000 residents),⁵ meaning that these three southern counties are sending relatively large portions of their populations to state prisons.

City trends

While incarceration affects every part of the state, it tends to be concentrated in a relatively small number of cities. Essex County — which contains the state’s largest city, Newark — has the third highest imprisonment rate among New Jersey counties at 351 per 100,000 residents. However, this burden is predominantly felt in Newark, which is home to 40% of the county’s population, but accounts for 66% of its residents who are in state prison. Similarly, 40% of Hudson County’s population reside in Jersey City (the state’s second largest city), but the city is home to 72% of people in prison from the entire county.

Neighborhood trends

Despite their geographic proximity, these two neighborhoods in Newark experience vastly different rates of incarceration: people in Belmont are four times more likely to be imprisoned than residents of University Heights.

Newark is one of the most racially segregated cities in the nation, in the most segregated county in New Jersey. And research has shown that policing tends to be concentrated in neighborhoods composed of people of color, in particular, Black people. This is true in Newark, where the city population is almost 50% Black, but Black people make up 75% of arrests. In 2020, Black people in the city were 1.6 times more likely to be stopped by police, 2.5 times more likely to be arrested, and 3.7 times more likely to be victims of police use of force than non-Hispanic white Newark residents.

With this in mind, it is not surprising to find imprisonment rates also tend to follow neighborhood divisions. While every neighborhood in Newark is missing some residents to state prison, the imprisonment rates vary widely.

Over half of everyone in state prison from Newark, for example, hail from just seven of the city’s 20 neighborhoods. All of those high-imprisonment rate neighborhoods are located in the southwestern corner of the city, are traditionally under-resourced, and have the highest population of Black residents in Newark. The disparities between these seven neighborhoods and other areas of the city are staggering: Belmont has an imprisonment rate of 1,302 per 100,000 residents, while on the other side of Springfield Avenue, University Heights has an incarceration rate of 327 per 100,000. In other words, people in Belmont are more than four times more likely to be imprisoned than residents of University Heights. With this context, it’s clear that specific neighborhoods — especially predominantly Black neighborhoods — are overpoliced and disproportionately affected by mass incarceration.

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

What are the differences between high- and low-incarceration communities?

Across the country, researchers have connected high local incarceration rates with a host of negative outcomes for the people who live there. In a prior Prison Policy Initiative analysis of 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.

Research has revealed similar correlations⁷ in communities around the country:

• Life expectancy: A 2021 analysis of New York State census tracts found that tracts with the highest incarceration rates had an average life expectancy more than two years shorter than tracts with the lowest incarceration rates, even when controlling for other population differences.⁸ And a 2019 analysis of counties across the country revealed that higher levels of incarceration are associated with both higher morbidity (poor or fair health) and mortality (shortened life expectancy).
• Community health: A nationwide study, published in 2019, found that rates of incarceration were associated with a more than 50% increase in drug-related deaths from county to county. And, a 2018 study found that Black people living in Atlanta neighborhoods with high incarceration rates are more likely to have poor cardiometabolic health profiles.
  An analysis of North Carolina data from 1995 to 2002 revealed that counties with increased incarceration rates had higher rates of both teenage pregnancy and sexually transmitted infections (STIs). A 2015 study of Atlanta also found that census tracts with higher rates of incarceration had higher rates of newly diagnosed STIs.⁹
• Mental health: A 2015 study found that people living in Detroit neighborhoods with high prison admission rates were more likely to be screened as having a current or lifetime major depressive disorder and generalized anxiety disorder.
• Exposure to environmental dangers: A 2021 study found that people who grew up in U.S. census tracts with higher levels of traffic-related air pollution and housing-derived lead risk were more likely to be incarcerated as adults, even when controlling for other factors.
  In New York City, neighborhood incarceration rate is associated with asthma prevalence among adults. Similarly, in a 2020 Prison Policy Initiative analysis of New York City neighborhoods, we found higher rates of asthma among children in communities with high incarceration rates.¹⁰
• Education: In a 2020 Prison Policy Initiative analysis of incarcerated New Yorkers’ neighborhoods of origin, we found strong correlation between neighborhood imprisonment rates and standardized test scores.¹¹ And a 2017 report on incarceration in Worcester, Mass., found that schools in the city’s high-incarceration neighborhoods tended to be lower-performing. What’s more, students in those neighborhoods faced more disciplinary infractions.
• Community resources and engagement: A 2018 study found that, throughout the country, people who are formerly incarcerated (as well as people who have been arrested or convicted of a crime) are more likely than their non-justice-involved counterparts to live in a census tract with low access to healthy food retailers. And the 2017 report on Worcester, Mass., revealed that high-incarceration neighborhoods had lower voter turnout in municipal elections.

We already have this wealth of data showing that incarceration rates correlate with a variety of barriers and negative outcomes. The data in this report build on this work by helping identify which specific neighborhoods throughout New Jersey are systematically disadvantaged and left behind. New Jersey 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.

Implications & uses of these data

The 8 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 programs that help prevent involvement with the criminal legal system, such as offices of neighborhood safety, community-based anti-violence programs and mental and behavioral health response teams that work independently from police departments. As outlined in the New Jersey Institute for Social Justice’s Refunding Communities: A Pathway Forward to Real Public Safety report, anti-violence programs and behavioral health first responder programs have worked across the nation as alternatives to the traditional law enforcement response. The data can also help guide reentry services (which are typically provided by nonprofit community organizations) to areas of New Jersey that need them most.

But even beyond the obvious need for reentry services and other programs to prevent criminal legal system involvement, 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 do return home) face a host of reentry challenges and collateral consequences of incarceration, including difficulty finding employment and a lack of housing. People impacted by the criminal legal 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. Lastly, investing in core community resources to mitigate structural issues like poverty, such as housing and healthcare, will reduce vulnerabilities for criminal legal system contact.

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 New Jersey Institute for Social Justice recently released a report, $600k to Damage Our Kids Forever: A Youth Incarceration Disaster, outlining the devastating financial and psychological toll of youth incarceration to youth and their families. The information and data in this current 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.

Methodology & data

This report capitalizes on the unique opportunity presented by New Jersey ending prison gerrymandering, which allows us to determine accurately for the first time where people incarcerated in state prisons come from. In this report’s linked datasets, we aggregate these data by a number of useful state-wide geographies such as counties, zip codes, and legislative districts and for some city geographies such as Newark and Jersey City 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, or neighborhood, 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.

Other data uses Notes on using this data to talk about other populations

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.

How we processed the data

New Jersey’s law ending prison gerrymandering required the Department of Corrections 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:

1. Downloading the New Jersey’s adjusted redistricting data, which contains the state’s entire population, with the people incarcerated in state prisons reallocated to their home addresses.
2. Subtracting the state’s redistricting data from the original Census Bureau P.L. 94-171 redistricting data, to produce a file that represented the number of incarcerated people the state determined were from each census block state-wide. (Census blocks that showed a net gain of population following the reallocation were the Census blocks that incarcerated people were reallocated to, and the amount of that change was the number of people from that block who were incarcerated in a state prison on Census day.) For a different analysis that focused on both the net gains and net decreases in individual census blocks and then aggregated to counties and the final redistricting plans, see Peter Horton’s report for Redistricting Data Hub on New Jersey.
3. Aggregating these block-level counts of incarcerated people to each of the geography types available in the report. In cases where a census block containing an incarcerated person’s home address straddles the boundary between two geographies, the incarcerated population was applied to the geography that contained the largest portion of the census block’s area.
4. Calculating imprisonment rates for each geography, by first calculating a corrected population that shows the Census 2020 population plus the number of incarcerated people from that geography; and then dividing the number of incarcerated people by the corrected total population, and then multiplied it by 100,000 to get an imprisonment rate per 100,000.

Important context and limitations on this data

Our analysis in this report documents the home addresses of 16,198 people in state prisons, which is somewhat less than the state’s total prison population of 18,109 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 New Jersey, 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 16,198 people when they may be aware that the state prison system had 18,109 people on Census Day:

• Some people in New Jersey state prisons are from other states and therefore were not reallocated to homes in New Jersey.
• Some addresses were unknown or could not be located for the reallocation. For example, an address on file may be incomplete or may contain only the notation “homeless” which of course cannot be applied to a specific home census block.
• Anyone whose home address by coincidence happens to be in a census block that contains a correctional facility would have been properly reallocated for purposes of ending prison gerrymandering, but their presence at that location would not, because of how we created our dataset, be apparent in this report.

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:

• Incarcerated in a federal prison, because states do not have the power to require home address data from federal agencies. The New Jersey legislation requires the state to request this data from the federal Bureau of Prisons, but that federal agency refused to share it.
• Incarcerated in another state’s prison system. States cannot require other states to share this information, and the fact that so many states are ending prison gerrymandering is too new of a phenomenon for them to have had the chance to enter into inter-state data sharing agreements.
• Incarcerated in a local jail, in this state or elsewhere; because the state’s effort to remedy prison gerrymandering was focused on state prisons.

About the geographies

We have 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 in some cities 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 16,198 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.

   

Footnotes

1. 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 reports on California, Colorado, Connecticut, Delaware, Maryland, Montana, Nevada, 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).  ↩

2. Unfortunately, neighborhood-level analyses are not possible for all large cities in the state. For example, the City of Paterson (the third largest city) does not officially recognize neighborhoods and therefore has no agreed-upon geographies for us to use to analyze neighborhood-level incarceration rates. However, for a local-level analysis of incarceration trends in Paterson and other cities, imprisonment rates by census tract are available in the appendix.  ↩

3. Essex County’s imprisonment rate is the third highest in the state with 351 people in state prison per 100,000 residents. Camden County’s imprisonment rate is the fourth highest in the state, with 345 people in state prison per 100,000 residents.  ↩

4. Cumberland County’s imprisonment rate is more than twice that of the state of New Jersey, with 444 people in state prison per 100,000 county residents. Cape May County’s imprisonment rate is 271 per 100,000 and Salem County’s imprisonment rate is slightly less, with 231 people in state prison per 100,000 county residents. Cumberland County and Salem County are both considered relatively rural and poor, with higher percentages of people living in poverty than the statewide average. In Salem County, the portion of the population that is Black is relatively consistent with the statewide population at 15%. Cumberland County has a much larger portion - in comparison to the rest of the state - of Black residents (22% compared to the state’s 15%) and Hispanic or Latino residents (32% compared to the state’s 21%). On the other hand, Cape May County is predominately white (92% compared to the statewide average of 72%), has a median household income about 1.3 times higher than that of Salem County, and has a lower percentage of residents in poverty than both Cumberland and Salem counties.  ↩

5. As explained in the methodology, this report’s imprisonment 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 New Jersey 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 145 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 341 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.  ↩

6. 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.  ↩

7. 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.  ↩

8. We also know that people who have been incarcerated have a shorter life expectancy than people who have not.  ↩

9. There are many additional studies linking incarceration rates and high community rates of STIs, including gonorrhea and chlamydia in North Carolina.  ↩

10. 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), 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.  ↩

11. 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.  ↩

12. Three state prison facilities - South Woods, Southern State, and Bayside - are located in Cumberland County. According to the New Jersey Department of Corrections’s 2010 county of commitment report, the total prison population across those three facilities on January 1, 2010 was 8,128, representing almost 48% of the total state prison population.  ↩

13. N.J. Rev. Stat.S 52:4-1.1-52:4-1.5 (2020).  ↩

14. 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.  ↩

See the footnotes

       

Acknowledgments

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.

We would also like to gratefully acknowledge the generous support of the Ford Foundation and the Fund for New Jersey.

About the authors

Emily Widra is a Senior Research Analyst at the Prison Policy Initiative. She is the co-author of States of Incarceration: The Global Context 2021. She is the organization's expert on health and safety issues behind bars, including the coronavirus in prisons. Her previous research also includes analyses of mortality in prisons and the combined impact of HIV and incarceration on Black men and women.

Henal Patel is the Director of the Democracy & Justice Program at the New Jersey Institute for Social Justice. Before joining the Institute, Henal was an associate at McElroy, Deutsch, Mulvaney & Carpenter. Previously, Henal had the honor of serving as a law clerk to Chief Justice Stuart Rabner on the New Jersey Supreme Court. While in law school, Henal was an Eagleton Institute of Politics fellow, participated in the Constitutional Litigation Clinic, and served as an assistant to the Chairman of the New Jersey Redistricting Commission. Henal received her J.D. from the Rutgers University School of Law - Newark and B.A. from Rutgers University. Henal serves on the Board of Directors at the League of Women Voters of New Jersey.

Ronald Pierce is a Policy Analyst at the New Jersey Institute for Social Justice. Ron is a frequent commentator and lecturer on issues related to voting rights, reentry, and the human rights of the incarcerated. His writing has been published in NJ Spotlight and Truthdig. Ron graduated from Rutgers University-Newark Summa Cum Laude in 2018 and was a recipient of the Vera Institute Scholarship.

About the organizations

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 with the publication of Importing Constituents: Prisoners and Political Clout in New York. This report demonstrated how using Census Bureau counts of incarcerated people as residents of the prison location dilutes the votes of state residents who do not live next to prisons, in violation of the state constitutional definition of residence. Since then, New Jersey is one of over a dozen states that have used Prison Policy Initiative's research to end prison gerrymandering.

Established in 1999 by Alan V. and Amy Lowenstein, the New Jersey Institute for Social Justice's cutting-edge racial and social justice advocacy seeks to empower people of color by building reparative systems that create wealth, transform justice and harness democratic power — from the ground up — in New Jersey. Known for its dynamic and independent advocacy aimed at toppling load-bearing walls of structural inequality to create just, vibrant and healthy communities, the New Jersey Institute for Social Justice committed to exposing and repairing the cracks of structural racism in our foundation that erupt into earthquakes in communities of color. The Institute advocates for systemic reform that is at once transformative, achievable in the state and replicable in communities across the nation.

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