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

by Emily Widra and Nick Encalada-Malinowski   Tweet this
June 2022
Press release

One of the most important criminal legal system disparities in New York 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

13 detailed tables to help you find incarceration data from your New York community

We created 13 different tables, each breaking down New York State’s population into different types of communities (such as counties or census tracts). Each table shows the number of people from each community known to be in the state’s prisons at the time of the 2020 Census.

This unique data source makes it possible to study imprisonment rates directly (rather than relying on prison admission and release data), and at more useful levels of analysis than just the county or zip code. Community advocates and policymakers can use these data to examine how incarceration impacts the communities they serve, as well as advocate for and inform decisions about changes that will best serve the needs of people in these communities.

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 New York with up-to-date data. New York 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 York’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 the redistricting data, we found that in New York, incarcerated people come from all over the state, but are disproportionately from specific cities and communities, often in the upstate region.4 While New York State incarcerates a smaller share of its residents than all but 7 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 New York City and also the smaller and historically under-resourced upstate cities and counties.

These data also allow us to understand better how incarceration rates correlate 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 programs and services housed outside the criminal legal system in the communities that need them most.

  • map of New York state showing incarceration rate by census tract and highlighting 8 counties with highest rates
  • map of New York city showing incarceration rate by neighborhood
  • map of Syracuse, New York showing incarceration rate by neighborhood
  • map of Buffalo, New York showing incarceration rate by neighborhood
  • New York
    State
  • New York
    City
  • Syracuse
  • Buffalo
   

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

At the broadest level, we find that people in New York state prisons come from every corner of the state. Every single county is missing a portion of its population due to incarceration.

County trends

The idea that incarceration is a problem unique to big cities is a myth, and our residence data shows that upstate community leaders should be worried about incarceration, too.

The two counties that top that list — Schenectady and Albany — have state prison incarceration rates of 484 per 100,000 and 340 per 100,000 respectively. In contrast, the state-wide incarceration rate is 193 people for every 100,000 residents,5 and the incarceration rate for Queens County (New York City’s borough of Queens) is roughly one fourth of Schenectady County and less than half of Albany County.6

Additionally, some of the least populous upstate counties—Montgomery, Fulton, Genesee, Yates, and Franklin—have some of the highest imprisonment rates in the state.7

City trends

New York City, by far the largest city in the state, has an imprisonment rate of 185 per 100,000. This is undoubtedly high, but it is much lower than many other cities across the state. The city of Rochester — the fourth most populous city in the state — with an incarceration rate of 1,051 per 100,000 city residents, is more than 5 times the rate in New York City. Syracuse — the fifth most populous city — has 864 people in state prison per 100,000 city residents, while the city of Albany has an incarceration rate of 917 per 100,000. Other, even smaller cities like Poughkeepsie and Schenectady experience disproportionate incarceration as well.8

Neighborhood trends

map comparing number of incarcerated residents of two neighborhoods in syracuse

Despite their geographic proximity, these two neighborhoods in Syracuse experience vastly different rates of incarceration: people in Southwest are 13 times more likely to be imprisoned than residents of Westcott.

Within cities and counties, incarceration tends to be concentrated in a relatively small number of geographic areas and neighborhoods — ones that tend to be systemically under-resourced. (And often, any investment these communities do receive is directed to policing, jails, and prisons.) Over a quarter of everyone in state prison from Syracuse, for example, hail from just four of the city’s 32 neighborhoods. All four of those high-incarceration rate neighborhoods — Southwest, Near Westside, Brighton, and Southside — are located just west of Interstate 81.9 The disparities between these four neighborhoods and other areas of the city are staggering: Southwest had an incarceration rate of 2,937 per 100,000 residents, while on the other side of Interstate 81, Westcott had an incarceration rate of 225 per 100,000. In other words, people in Southwest are more than 13 times more likely to be imprisoned than residents of Westcott.

Three of these four high-incarceration neighborhoods are home to the highest portion of Black residents in all of Syracuse. In Syracuse, Black people make up less than a third of the city’s population, but accounted for 79% of traffic stops and comprised 80% of marijuana-related arrests in the city. Given these startling racial disparities in policing, it is no surprise that more people are missing from Black neighborhoods in Syracuse than their white counterparts on the east side of I-81. With this context, it’s clear that specific neighborhoods — especially predominantly Black neighborhoods — are overpoliced and disproportionately affected by mass incarceration.

While all New York state 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.

   

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

We already know that communities in New York State (and around the country) with high incarceration rates simultaneously tend to face a wide range of other negative outcomes. A 2021 study, led by Dr. Louisa W. Holaday, found that New York census 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.10

In New York City, neighborhood-level incarceration rate is associated with asthma prevalence among adults. Similarly, in our previous analysis of New York City neighborhoods after the 2010 Census, we found higher rates of asthma among children in communities with high incarceration rates.11 This analysis also found a strong correlation between neighborhood imprisonment rates and standardized test scores.12 Using the data in this newest report, New Yorkers can now examine the data and find their own granular local-level and state-wide correlations and choose to allocate needed resources to places hardest hit by incarceration.

Even beyond the above studies of New York, researchers across the country have connected high local incarceration rates with a host of barriers and negative outcomes for the people who live there. In our own 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 correlations13 in communities around the country:

  • Life expectancy: 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 higher 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.14
  • 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 or 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.
  • Education: A 2017 report on incarceration in Worcester, Massachusetts, 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 formerly incarcerated people (as well as all people who have been arrested or convicted of a crime) throughout the country are more likely than their non-justice-involved counterparts to live in a census tract with low access to healthy food retailers. And the 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 York State are systematically disadvantaged and left behind.

   

Implications & uses of these data

The 13 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 and mental health response teams that work independently from police departments. The data can also help guide reentry services (which are typically provided by nonprofit community organizations) to areas of New York 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 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.

About New York’s law ending prison gerrymandering

This report uses the redistricting data produced by New York’s historic 2010 law ending prison gerrymandering. “Prison gerrymandering” is the practice of drawing representative districts that count people in prison as legal residents of the prison, thereby inflating the political clout of people in districts with prisons, and diluting the influence of residents in all other districts. It is the result of a longstanding flaw in the U.S. Census, which counts incarcerated people as residents of their prison or jail cells on Census Day.

Ideally, the Census Bureau would update its methodology for this era of mass incarceration by counting imprisoned people at home. When the Bureau rejected calls to fix the problem for the 2010 Census, New York became the second state to develop and enact creative state-level legislative solutions to correct this flaw in the Census Bureau’s data thus ending prison gerrymandering in New York.

This problem of “prison gerrymandering” was particularly stark in New York State. At the time of the 2000 Census, the majority of the state’s incarcerated people came from New York City, but virtually all — 98% — were incarcerated in disproportionately white State Senate districts. In sum, seven upstate New York State Senate districts met federal minimum population requirements only because they used incarcerated people as padding. Five of those Senators sat on and controlled the state’s powerful Crime Committee and Codes Committees, responsible for the criminal law and prison construction.15 The conflict of interest was obvious, as one of the State Senators even boasted that he was glad that the 9,000 people confined in his district could not vote because “they would never vote for me.”

But if prison gerrymandering seemed harmful to democracy in the State Senate, the problem was even larger for some of the upstate communities that hosted prisons. For example, half of the population of one city ward in Rome, New York was incarcerated at two state prisons, which gave the residents of the prison district twice the influence of the residents of other city council districts not similarly padded with a prison.

New York’s law to end prison gerrymandering ultimately passed on a narrow partisan vote, but the law was broadly supported by the public. A Quinnipiac University poll shows it was supported by the majority of the state, urban and rural, Democrat and Republican, and the bill received editorial support from urban and rural upstate papers.16

   

Methodology & data

This report capitalizes on the unique opportunity presented by New York’s ending of 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, legislative districts, school districts, and cities, and city-wide geographies like neighborhoods, city council districts, and health districts.

This section of the report discusses how we processed the data, some important context and limitations on those data, and some additional information 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, school district, or other breakdowns and want to add imprisonment data to your analysis, we probably have exactly what you need in a prepared appendix table.

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. Those states could 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 York’s law ending prison gerrymandering required the New York State Department of Corrections and Community Supervision (DOCCS) 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 were 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 New York’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 York.
  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.17
  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 multiplying it by 100,000 to get an imprisonment rate per 100,000.

Important context and limitations on these data

Our analysis in this report documents the home addresses of 39,027 people in state prisons, which is somewhat less than the state’s total prison population of 42,492 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 York, the state’s reallocation efforts were an unqualified 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 those data to discuss the concentration of incarceration, some readers may want to be aware of some of the reasons why our report discusses the home addresses of 39,027 people when they may be aware that the state prison system had 42,492 people on Census Day:

  • Some people in New York State prisons are from other states and therefore were not reallocated to homes in New York State.
  • 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. (However, from our review of New York’s documentation on their reallocation, it appears to us that the state has made considerable progress at improving the quality of its data over the last decade.)

Similarly, this report doesn’t reflect the other groups of people incarcerated from particular communities who are not reflected in these data,18 because they were:

  • Incarcerated in a federal prison, because states do not have the power to require home address data from federal agencies.
  • 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’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 these 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, school 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 39,027 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 are 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 New Jersey and Maryland.

    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. Neighborhood Tabulation Areas (NTAs) are geographies created by the City of New York from whole census tracts as a way to approximate neighborhoods with an intended minimum population of 15,000. In our appendix table and map, we excluded non-neighborhood geographies like cemeteries, airports, Rikers Island, and parks.  ↩

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

  4. The patterns of incarceration in New York State have changed over the last two decades, and various changes in criminal legal policy and practice in New York City mean that the city is no longer home to a disproportionate share of the state prison population. In our 2002 report, Importing Constituents: Prisoners and Political Clout in New York, we found that 66% of people in New York prisons were from New York City. And, in a detailed analysis of New York prison populations from 2000 to 2009, the Brennan Center reported that the 17% reduction in the state’s prison population was driven by the reduction in people sent to prison from New York City. Their findings suggest this large decline in prison admissions from New York City was driven by changes in arrest and prosecution procedures, while prison admissions for felony convictions outside of New York City increased. Similarly, the Correctional Association of New York reported in 2019 that various policy and practice changes in New York City reduced both arrests and cases resulting in a prison sentence; these reductions led to a shift over the last decade, so that the majority of people incarcerated in New York now originate outside the city. Our analysis of 2020 Census data supports this finding: 42% of New York’s incarcerated population originated in the five boroughs, and 58% from other parts of the state.  ↩

  5. 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 New York 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 224 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 376 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. The imprisonment rate in Queens County — 121 per 100,000 residents — is lower than 52 other counties in New York.  ↩

  7. These five counties are in the top third highest imprisonment rate counties in New York, with incarceration rates ranging from 312 per 100,000 in Montgomery County to 250 per 100,000 in Franklin County.  ↩

  8. In fact, research suggests that smaller cities are the new frontier of mass incarceration. In a 2017 study in Massachusetts, for example, researchers found the highest incarceration rates in suburbs and regional cities.  ↩

  9. The historic I-81 division of Syracuse is not insignificant: the east side is made up of university student housing, maintained green spaces, and a wall blocking the highway view, while the west side consists of predominantly low-income neighborhoods with much larger Black populations. The New York Civil Liberties Union describes Syracuse as “among the top ten most segregated metro areas in the country.” Racial and environmental justice advocates have long been vocal about the negative consequences of the I-81 division of Syracuse, and now we know this division is also significant when looking at neighborhoods that are missing the most people to incarceration in state prison.  ↩

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

  11. 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.  ↩

  12. 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.  ↩

  13. 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.  ↩

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

  15. In 2003, the Crime Committee was chaired by Senator Nozzolio (District 54) and Districts 49, 47, 48, and 59 were also on the committee. That same year, the Codes Committee was chaired by Senator Volker (District 59) and Districts 45 and 47 were also on the committee.  ↩

  16. See, e.g., In New Census, Home is Where the Vote Should Be, Times Herald Record, Feb. 19, 2010; Prison-based Gerrymandering Should be Abolished, The Daily Review, Aug. 7, 2010; Jim McGrath, Prison Politics in a New Light, Times Union, Aug. 6, 2010; Our View: Don’t Count Prisoners with Voters, Utica Observer Dispatch, Feb. 26, 2010; Reform Redistricting in New York, The Post-Standard Editorial Board, June 30, 2010.  ↩

  17. For the school district geography, we had to do one additional step because in that file, a few individual school districts had some slight overlaps. Because this could - in theory - cause us to accidentally reallocate the same person to multiple individual school districts, we first modified the geographies so that the small overlapping portion would not impact the determination of which block a geography was applied to.  ↩

  18. 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.

 

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.

Nick Encalada-Malinowski is the Civil Rights Campaign Director at VOCAL-NY, where he has worked for 5 years leading the organization’s campaigns to confront and mitigate mass incarceration. He is an organizer, writer, and social worker based in Brooklyn, New York.

 

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, over a dozen states, including New York have used Prison Policy Initiative’s research to end prison gerrymandering. Today, roughly half of the country now lives in a place that has formally rejected prison gerrymandering.

VOCAL-NY is a statewide grassroots organization working to create healthy and just communities by building power among some of the most marginalized New Yorkers, including low-income people affected by HIV/AIDS, drug use, incarceration, and homelessness. VOCAL-NY accomplishes this through community organizing, leadership development, advocacy, participatory research, and direct services. By combining issue-specific campaigns that directly benefit the lives of its members with low-threshold harm reduction services, the organization endeavors to address the problems its members face in both the immediate and long-term.



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