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by Wanda Bertram, February 13, 2025

Decision-makers often cite worries about recidivism as a primary reason to oppose criminal legal system reforms. These worries are caused by both the concept of the “revolving door” of incarceration and by politicians’ fears that a single violent recidivism event will hurt them politically. The realities of recidivism, though, are complex, and the more advocates know about the facts of how many people return to prison and what those numbers mean, the better equipped they can be to help politicians make informed decisions about policy.

Earlier this month, we released a new guide to recidivism statistics and their history, and how advocates for decarceration can challenge the way these flawed statistics are used to undermine their efforts. The new guide covers:

  • The history of the “Willie Horton Effect,” why the power of political backlash against reform is overhyped, and how advocates should respond when lawmakers are swayed by isolated stories of recidivism.
  • The different types of recidivism metrics and what they mean, how and why to be cautious about commonly-cited statistics, and the role of “technical” probation and parole violations and minor offenses in driving recidivism.
  • Recidivism statistics related to people convicted of violent/sexual offenses, in the context of common arguments for “carving out” these individuals from criminal legal reforms.
  • How advocates can push lawmakers to consider other metrics of post-release success besides recidivism, focusing on a person’s quality of life and contributions to their community.

We’ll also be hosting a webinar at 1 PM EST on Wednesday, March 19, where our Policy and Advocacy Manager Sarah Staudt will discuss pushing back against unproductive and inaccurate uses of recidivism stories and statistics. Advocates, journalists, and members of the public are invited to attend.

Register here


Recidivism webinar promotional image

This guide is part of our ever-expanding Advocacy Toolkit, a series of resources for criminal legal reform advocates based on our own research and advocacy.


Our analysis of Jail Data Initiative data confirms the troubling practice of shuffling unhoused people into jails, at enormous moral and fiscal cost.

by Leah Wang, February 11, 2025

Local jails, which hold one out of every three people behind bars, have become America’s misguided answer to problems faced by the most vulnerable people, like poverty and homelessness. Despite jails’ central role in mass incarceration, comprehensive national data about the 5.6 million people who cycle through them each year is collected infrequently, leaving even basic questions about jails unanswerable.1 Fortunately for researchers, advocates, journalists and many others, the Jail Data Initiative is collecting present-day data from roughly 900 jails to provide a better understanding of those who are criminalized and locked up, including the approximately 205,000 unhoused people who are booked into jails each year.

In this briefing, we present what we know about unhoused people who are booked into jails, using the best available dataset, collected from jail rosters2 by the Jail Data Initiative (JDI). (Last year we published our first analysis of JDI data, focused on repeat bookings; we intend to publish additional analyses this year.) We find that people booked into jail who were marked as unhoused at intake are held for longer than average, while being handed some of the lowest-level charges like trespassing or petty theft.

As we’ll explain, the data have limitations, and some jails are simply not collecting important demographic data such as housing status. But we know that jurisdictions have grown increasingly hostile toward people with nowhere to call home: Instead of extending a helping hand to people simply trying to rest, eat, or otherwise survive, local law enforcement is handing them a criminal record and further destabilizing their lives.

 

  • bar chart showing that unhoused people account for 4.5% of jail bookings, but 20% of bookings with trespassing top charges
  • bar chart showing that people identified as unhoused make up just 4 percent of jail admissions, but 42 percent of those unhoused people are booked into jail multiple times in a year, compared to 20% of people who were housed or had unknown housing status
  • bar chart showing that unhoused people account for 4.5% of jail bookings, but 20% of bookings with trespassing top charges
  • bar chart showing that people identified as unhoused make up just 4 percent of jail admissions, but 42 percent of those unhoused people are booked into jail multiple times in a year, compared to 20% of people who were housed or had unknown housing status

Key findings

Only 20% of the jail rosters in the full dataset (175 of 889) contained one or more entries indicating an unhoused person, but the data from those jails suggest that cities and counties are turning to their jails to address behaviors that unhoused people often engage in because they are unhoused and/or poor.

Note: When referring to “unhoused people,” we mean those who are known to us to be unhoused, based on the jail roster data; everyone else may or may not have housing, but it’s unknown. As such, we also don’t know about people entering jails who are facing housing insecurity. For more information on our process, see our methodology section.

  • About 4.5% of jail bookings in our sample are of unhoused people: Across the 175 jail rosters in our dataset, there were 22,839 bookings of people known to be unhoused, out of 503,571 total bookings over the course of one year. These bookings represent over 15,000 unique unhoused individuals (and about 406,000 people whose housing status was unknown, or who were housed, before their admission to jail.) This translates to about 205,000 different unhoused people going to jails each year nationwide — nearly one-third of the number of people experiencing homelessness on a single night in 2023.3
bar chart showing that unhoused people account for 4.5% of jail bookings, but 20% of bookings with trespassing top charges
  • Unhoused people are more likely to be booked multiple times: More than one out of every five jailed people are booked again within a year. Unhoused people made up a disproportionate share of those rebooked, representing 4% of all unique jail bookings but 8% of those rebooked. Said another way, over 40% of unhoused people booked into jail were booked multiple times, while only 20% of people who were housed or had an unknown housing status were booked multiple times. This finding affirms many observations of ineffective targeting and sweeps of homeless populations.
  • Unhoused people are held in jails for longer than average: The overall average stay in jails whose rosters included at least one unhoused person was 21 days, but for unhoused individuals was 32 days — almost 50% longer. We also looked at median length of stay, because the average could be skewed by very long or very short jail stays. The median length of stay for all bookings in this sample was 4 days, but for unhoused individuals was 14 days — which is 2.5 times longer. Our analysis didn’t include bond (bail) amounts, but it’s safe to assume that unaffordable cash bail is keeping many unhoused people in jails longer than those who can afford it.
  • People aged 55 and older make up a disproportionate share of bookings of unhoused people: About 10% of all jail bookings in our sample were older people (those age 55 or older), but 15% of bookings of unhoused people were older people. It’s important to note that older adults are more likely to spend 50% or more of their income on rent compared to people in other age groups, making them severely housing-cost-burdened and closer to housing insecurity or homelessness.
bar chart showing that unhoused people have a median length of stay in jail of 14 days while people with housing or an unknown housing status have a median length of stay of 4 days
  • The mass jailing of unhoused people overburdens Black people: While Black people accounted for 31% of all bookings, they accounted for 40% of all bookings of unhoused people. Meanwhile, white people made up 62% of all bookings but only 55% of all bookings of unhoused people. Similarly, people of color are overrepresented in the unhoused and severely housing-cost-burdened populations.
  • Unhoused people face a litany of unfair criminal charges simply because they’re unhoused: In general, most people are jailed on public order, property, or drug charges, but bookings of unhoused people made up a disproportionately large share (8%) of bookings where the most serious charge was a property charge, and a slightly greater-than-expected portion (4.8%) of bookings for which the most serious charge was a drug charge. Unhoused people were most commonly booked for a top charge of trespassing — a charge frequently used to criminalize people for having nowhere else to go. They were also more commonly booked for possession of amphetamines, disorderly conduct/drunkenness, and petty theft (of less than $500) compared to all jail bookings in our sample. In contrast, bookings of unhoused people made up disproportionately small shares of bookings where the top charge was “violent” (3%), or related to DUI (<1%) or criminal traffic (2.1%) offenses.

Inconsistent data collection in jails leaves gaps in understanding

Although the data suggest that U.S. cities and counties are unnecessarily and excessively jailing unhoused people, 4% of jail bookings is a significant underestimate of unhoused people in local jails. Our methodology relies on positively identifying people as unhoused, but many more unhoused people may have chosen to list a shelter address, a family member’s address, or another location as their address when they were booked into jail.

And clearly, housing and other demographic data are not consistently collected by jail jurisdictions. While jail rosters are by no means a traditional source of data, it’s telling that only 20% of the nearly 900 rosters in the Jail Data Initiative’s sample recorded even a single person as unhoused during the yearlong study period. Smaller jails, in particular, were underrepresented in our dataset and may be less likely to record housing status information: Jails with an average daily population of less than 100 people made up 26% of our dataset, but make up 54% of jails across the U.S.

Criminalization will never solve homelessness

While not the complete picture of jails that we all wish for, the Jail Data Initiative data provide the best and most recent look at our national reliance on jails for addressing the ongoing crisis of homelessness. Our analysis reveals that unhoused people in jails are kept there for longer, are more likely to be booked multiple times, and are disproportionately Black. In total, over 200,000 unhoused people are coming in contact each year with law enforcement agents who are supposed to be keeping them safe, but the thinly veiled case for bringing them to jail only exacerbates their homelessness4 and despair.

There may be reports of unhoused people “choosing” to go to jail over sleeping in the streets, suggesting that jail is an acceptable solution. But it’s been shown time and time again that providing housing, services, and treatment instead of jail incarceration is more sustainable, a huge relief for taxpayers, and much less harmful to individuals. This is where diversion programs and permanent supportive housing can be utilized, before someone is arrested — better yet, before any police encounter.

Methodology

The Jail Data Initiative (JDI) collects, standardizes, and aggregates individual-level jail records from more than 1,000 jails in the U.S. every day. These records are publicly available online in jail rosters — the online logs of people detained in jail facilities that often include some personal information like name, date of birth, county, charge type, bail bond amounts, and more. JDI uses web scraping — the process of automating data collection from webpages — to update their database of jail records daily. The more than 1,000 jails included in the JDI database represent more than one-third of the 2,850 jails identified by the Bureau of Justice Statistics’ Census of Jails, 2019 and are nationally representative.

For the purposes of our analysis of unhoused populations, we limited the JDI sample to bookings with admission dates between July 1, 2023 and June 30, 2024 from 175 jail rosters for which at least one person was categorized as “unhoused” upon intake (except when looking at rebookings; see below). To do so, our partners at JDI searched parts of the “Address” field in jail rosters for words like “homeless,” “unhoused,” “transient,” and similar keywords, then dropped rosters and/or bookings that did not meet our standards for robustness.

In all, there were 503,571 jail bookings captured across these 175 rosters, representing over 420,000 unique individuals booked into jail. Because our sample of jails for this analysis is so much smaller than the full JDI sample, ours may not be nationally representative.

Of course, not all of the jails included in the Jail Data Initiative database provide the same information. For the more detailed analyses of jail bookings by demographic and other characteristics, we used subsets of this sample due to inconsistencies in data collection:

  • Length of stay: This sample included 440,120 bookings from 175 jail rosters.
  • From the original sample described above, bookings were removed due to potential issues with date range overlap or missingness. Next, any active bookings as of the end of the date range (2024-06-30) were excluded.
  • Rebookings: This sample included 599,423 bookings from 140 jail rosters. To look at unhoused people booked into jail multiple times, we began with data from 648 jail rosters for which there was available data for a two-year window (July 1, 2021 to June 30, 2023), plus an additional 365 days for a look-forward review of rebookings (to June 30, 2024). We looked at people who were both booked into jail and released within the two-year study period, and counted people as “rebooked” or “booked two or more times” if they were booked into the same jail system within 365 days of their first jail admission in the study time period. We elected to use a two-year time frame to capture a larger sample of bookings than we could in a single calendar year. From this sample of 648 jail rosters, there were 140 rosters that included at least one individual categorized as unhoused upon admission for any of their bookings.
  • Gender: While we did look at the gender distribution of unhoused bookings, we did not find a notable difference between bookings of unhoused people and those whose housing status was unknown. The sample here included 477,363 bookings from 167 jail rosters, where at least one person was categorized as unhoused and where sex and/or gender was also reported.
  • Race and ethnicity: This sample included 401,544 bookings from 138 jail rosters, where at least one person was categorized as unhoused and where race and/or ethnicity was also reported.
  • Age: This sample included 448,273 bookings from 155 jail rosters, where at least one person was categorized as unhoused and where age was also reported.
  • Charge type: This sample included 437,241 bookings from 173 jail rosters where at least one person was categorized as unhoused and where the charge type was also reported. Charges were standardized by JDI into both broad categories (Violent, Public Order, Property, Drug, DUI Offense, and Criminal Traffic) and more specific offense types, as described by the Uniform Crime Classification Standard (UCCS) schema. An overall “top charge” category per person was determined by selecting the most severe charge from among all bookings for an individual.

For more information on how JDI standardizes the terms in their data, please see their documentation page at https://jaildatainitiative.org/documentation/glossary.

See full Methodology

Footnotes

  1. Unbelievably, the 2002 Survey of Inmates in Local Jails (SILJ) is the most recent, nationally representative data available on people held in local jails (whereas an annual Survey of Jails and occasional Census of Jails capture some demographic information, but only from administrative records). The SILJ collects information like who is held pretrial due to inability to afford bail; the racial distribution of people detained pretrial; and what offenses people are locked up for before trial. The next edition of the SILJ was sent out to respondents in late 2024, a full 17 years off-schedule.  ↩

  2. A jail roster is a publicly available, online log of all individuals detained in a jail facility (or in some cases, multiple facilities or counties) on a given date. Jail rosters are typically updated daily, hourly or even in real-time, and contain information obtained at booking, like someone’s basic identifying information, where they were arrested, and the dollar amount of their bond.
     ↩

  3. To estimate the number of different (unique) unhoused people booked into jail in a year, we started with the share of unique individuals in our sample, 3.63% (or 15,297) who were known to be unhoused. We applied this percentage to the number of unique individuals booked over the year from July 1, 2022 to June 30, 2023, which was 5,658,992, yielding our estimate of 205,268.
     ↩

  4. There isn’t a plethora of research showing that jail time sustains homelessness — though studies out of Colorado and New York City suggest this is the case — but prison incarceration increases one’s likelihood of homelessness upon release by ten times.  ↩


by Sarah Staudt, February 6, 2025

Yesterday, Prison Policy Initiative’s Advocacy Director, Sarah Staudt, testified in the House Judiciary Committee in the Colorado Legislature to support a bill that would guarantee visitation rights to people in Colorado prisons.

HB25-1013, sponsored by Representatives Regina English and Jennifer Bacon, would make visitation a right, not a privilege, for people in Colorado prisons. While the Department of Corrections would maintain the ability to restrict visitation for safety reasons, visitation would no longer be able to be taken away for disciplinary reasons, like as punishment for refusing work within the prison.

At the request of Together Colorado, we provided testimony about the wealth of research that shows that visitation is vital for helping incarcerated people maintain their mental health, reintegrate into society, and avoid returning to the criminal legal system.

Visitation has numerous benefits for incarcerated people, including decreasing recidivism; people who experience visitation were 25% less likely to be rearrested within two years of release from prison. Visitation also improves the likelihood of employment after release. Incarcerated people who had family visitation had odds of finding employment almost 2 times higher than those who were not visited by family. Lastly, visitation helps incarcerated people cope with the inherent stressors of incarceration, decreasing mental health issues.

Visitation is also a key tool in decreasing the harm that incarceration causes to children and families beyond prison walls. Nationwide, half of people in prison are parents to minor children, including 80% of all incarcerated women. Incarceration of a parent is a stressor for children that affects overall wellbeing, family dynamics, poor school performance, and a heightened risk of eventual involvement in the criminal legal system. Visitation with family has been shown to lessen these negative outcomes.

Prison Policy Initiative is proud to support HB25-1013, and hopes that it can serve as a model for legislatures around the country to improve access to visitation for incarcerated people.


A little-known 1988 law called the Thurmond Amendment stripped people with drug distribution convictions of federal protections under the Fair Housing Act, making it even more difficult for many people with criminal records to secure housing - even when they are qualified in every other way, and even when the conviction is decades old. By our count, this law makes it more difficult for as many as 3 million people with these kinds of convictions to secure housing.

by Wendy Sawyer, February 5, 2025

You’ve probably never heard of the Thurmond Amendment, but for almost 40 years, it has been quietly enabling landlords to deny housing to people based solely on a past conviction for selling drugs — no matter how qualified they are as tenants, no matter what drugs or quantities were involved, and no matter how long ago they were convicted. This lifelong collateral consequence, tied to this one specific type of conviction, makes it even more difficult for people with criminal records to find housing at a time when it’s already a near-impossible task given the highly competitive rental markets in the U.S. As we and many other researchers have explained before, safe and stable housing is a critical factor in reentry success, while homelessness puts people directly in the crosshairs of law enforcement. These facts put the Thurmond Amendment directly at odds with correctional and public safety interests.

A coalition of advocates is working to repeal the law, led by a real estate investor who was directly impacted by the Thurmond Amendment. Their first step: gathering the available data about its impact and raising awareness of this overlooked relic of the failed “war on drugs.” That’s where we at the Prison Policy Initiative come in. One form of support we offer advocates — particularly through our Policy & Advocacy team — is to bring to light the relevant data that exists about an issue, and to find ways to fill in the gaps where the necessary information simply isn’t available. When the coalition came to us with the question of how many people are potentially impacted by the Thurmond Amendment, we combed through the available historical data to come up with an estimate, ultimately finding that over 3 million people in the U.S. have received drug distribution convictions since 1986 (which is as far back as the available data go).

How we developed our estimate

Our approach, sources, and assumptions

You might think it would be easy to answer the question, “How many people in the U.S. have a drug distribution conviction and could therefore be excluded from Fair Housing Act protections?” but the unfortunate fact is that criminal legal system data are rarely collected or reported in ways that provide simple answers to simple questions. In this case, we were lucky to find that the annual number of felony convictions in state courts for “drug trafficking” (manufacturing or distribution) was published every other year from 1986 to 2006; for federal court convictions, this number was published every year from 1990 to 2014. We found no data for years prior to 1986, and had to use less-relevant but related data to produce estimates for the missing years. Then, to avoid double-counting people who had more than one such conviction (because they would be excluded under the Thurmond Amendment for their first conviction), we had to estimate how many of these convictions were “firsts” for people as opposed to subsequent convictions of the same individuals. Missing from our analysis are people with only a misdemeanor drug distribution/manufacturing conviction (who are also excluded by the Thurmond Amendment), because we couldn’t find a data source on which to base an estimate of their number.1 Inevitably, because of the gaps in the available data, our estimates are conservative and inexact, but we believe they are the only ones produced to date. This is how we did it.

For convictions in state courts:

  • In even-numbered years from 1986 to 2006, the National Judicial Reporting Program reported estimated numbers of felony convictions based on a nationally representative sample of counties. These were published in a Bureau of Justice Statistics report series, Felony Sentences in State Courts.
  • For odd-numbered years from 1987 to 2005, we used the reported even-numbered year estimates to calculate the least squares regression line and interpolated values for the missing years along that line.
  • For the years 2007-2023, we calculated estimates based on (a) annual arrests of adults for drug trafficking and (b) the most recent known ratio of felony convictions for drug sale or manufacturing to arrests for drug trafficking, which was 62 per 100 arrests in 2009. However, the number of annual arrests specifically for drug trafficking are not reported; instead, the FBI reports the number of all drug arrests — combining both sale/manufacturing and possession — and the percentage of drug arrests that were for sale or manufacturing versus possession. Once we had estimates of how many people aged 18 years and older were arrested for drug-related offenses each year, we multiplied those estimates by the annual percentages attributed to sale/manufacturing to produce estimates of adult arrests specifically for drug distribution or manufacturing. 2

    We wanted to exclude people under the age of 18 from our estimates because minors are typically (though not always) referred to juvenile courts, where they would not receive a felony conviction that would exclude them from fair housing protections. But this, too, required a few steps. Because not every jurisdiction reports its arrest data to the FBI every year, the FBI reports arrest data by most serious charge in two ways: the reported number of arrests and the estimated number of arrests. The estimated number adjusts for jurisdictions that did not report their data, providing the FBI’s best estimate of how many arrests were made nationwide in a given year. Unfortunately, these estimates can’t be broken down in as much detail as the reported numbers are, by characteristics such as age or sex. However, relying only on the reported numbers would lead to a serious undercount of arrests: for almost every year from 2007 to 2023, for example, the reported total was roughly 20% to 30% lower than the estimated total for drug arrests. For this reason, we calculated our own estimate of adult drug arrests based on the percentage of reported drug arrests that involved adults for each year, multiplying the FBI’s estimated total drug arrests by the adult percentage, which was between 89% and 96% for all years.

    Once we had annual estimates of adult arrests for drug sale or manufacturing for each year, we multiplied those estimates by 62% (the most recently reported ratio of drug sale/manufacturing arrests that result in felony convictions) to estimate how many arrests led to felony convictions.3

  • Finally, to avoid double-counting people with multiple felony convictions for drug sale/manufacturing, we relied on the most recently reported percentage of people whose most serious arrest charge was drug trafficking who had no prior felony conviction, which was 51% (again, from 2009). We multiplied each of the annual estimates of felony convictions for drug sale/manufacturing by 51%, resulting in a conservative final estimate, since those previous felony convictions could be for any offense type, not necessarily for drug sale/manufacturing (the only felony convictions that would be disqualifying under the Thurmond Amendment). Our final estimate of first-time convictions for drug sale/manufacturing through state systems for 1986-2023 was approximately 3,023,773.
  • To varying degrees, these state-level estimates all rely on data from the National Judicial Reporting Program and/or State Court Processing Statistics Program, which in turn are based on data from a sample of the nation’s 75 largest counties. Crime and law enforcement patterns vary by urbanicity (that is, places that are more rural or suburban have different policing patterns than more urban jurisdictions), so our estimates are not as accurate as they would be if we had access to data from a broader range of counties. Unfortunately, that level of data collection has never existed at the national level, to our knowledge.

For convictions in federal courts:

  • For the years 1990-2014, the U.S. Sentencing Commission (USSC) published the number of felony convictions for drug “trafficking” (sale/manufacturing) in its Annual Reports and Sourcebooks. For the years 2015-2023, the USSC publishes the same data on its Dashboard.
  • For the years 2016-2023, the USSC Dashboard also reports the annual number of people sentenced for drug trafficking who had a prior conviction for drug trafficking, which we used to adjust for the double-counting of people who received more than one such conviction. We removed the reported annual number of people with prior drug trafficking convictions from the reported annual number of trafficking convictions for those years. For the previous years for which we could not find similar estimates (1990-2015), we removed 30.3% of the reported annual convictions — the average share of people with prior trafficking convictions reported for the years 2016-2023.4
  • Finally, we summed our annual estimates of first-time felony drug trafficking (sale/manufacturing) convictions for all years, giving us a total of approximately 483,643 people convicted through the federal system.

Our final national estimate is the sum of our state court and federal court estimates: 3,507,417 U.S. adults with felony convictions for drug distribution or manufacturing. This is likely a significant underestimate of the actual number of people denied legal protection for housing discrimination based on their conviction under the Thurmond Amendment, because at every decision point that would impact our final estimate, we erred on the conservative side.5

Understanding the Fair Housing Act and the Thurmond Amendment

The Fair Housing Act of 1968, a key piece of civil rights legislation, declared discrimination by housing providers on the basis of race, religion, sex, national origin, familial status, or disability illegal. The 1988 Fair Housing Amendments Act strengthened the Department of Housing and Urban Development’s (HUD’s) power to enforce the Act, creating a new avenue of legal recourse for tenants and homebuyers who experience discrimination when applying to rent an apartment, buy a home, or take out a mortgage.

Enacted at the height of the failed “war on drugs,” however, the 1988 law includes an amendment named for its sponsor, the segregationist Strom Thurmond, which explicitly denies fair housing protections to people who have been convicted of drug manufacturing or distribution. While this amendment may seem like an odd thing to tack onto civil rights legislation that does not explicitly protect people from discrimination based on criminal history, it creates a carveout that allows landlords to deny housing to this specific population. Because drug distribution convictions — and criminal records more broadly — disproportionately impact Black and Brown people, discrimination against all individuals with criminal records is effectively a form of racial discrimination.6 On this basis, when housing providers discriminate against people with criminal records, individuals can make “discriminatory effect” claims under the Fair Housing Act. However, when landlords discriminate against people with drug distribution convictions specifically, the Thurmond Amendment makes these claims impossible. No other category of criminal conviction is excluded in the same way.

Importantly, repealing the Thurmond Amendment would do nothing to diminish the autonomy of landlords and other housing providers. The Fair Housing Act doesn’t require anyone to provide housing to people with drug distribution convictions, or any other kind of conviction for that matter. It just encourages them to consider applications more fully instead of automatically disqualifying people on the basis of a criminal record alone.

We know better now: Lessons learned about drugs, crime, and housing

The Thurmond Amendment was an expression of “tough on crime” 1980s politics, which were rationalized by false beliefs about drugs, crime, and punishment. For instance, in a recent op-ed, Yusef Dahl, who has been leading the effort to repeal the Amendment, points to the misconception that people who sell drugs are different from people who use drugs, which was central to how Thurmond sold the amendment to the rest of Congress: “drug dealers,” he argued, don’t deserve federal protection. In reality, distributors and users are often the same people: the most recent national data show that 78% of people in state prisons whose most serious offense was drug-related 7 reported using any drug in the month before their arrest. More than half (55%) were using at the time of the offense itself. 8 Among people sentenced to local jails for drug-related offenses (i.e., those serving shorter sentences than people in prison), the most recent data show 74% met the criteria for a substance use disorder. While it may be rhetorically convenient for politicians to vilify people who sell drugs, doing so necessarily casts a wide net around drug users who are often coping with poverty and illness.

Second, the Thurmond Amendment’s complete exclusion of people convicted of drug distribution, no matter how long ago, implies a belief that people don’t change.9 Decades of criminological research on desistance (the individual process of shifting away from lawbreaking behavior) prove otherwise. In fact, among the recommendations of experts Shawn Bushway and Christopher Uggen, authors of the chapter linked above, is “eliminat[ing] most collateral consequences of criminal justice involvement,” such as barriers to housing. Putting a finer point on it, they write: “Policies that continue to center a criminal act years after that act was committed directly contradict everything we know about desistance.”

Ultimately, this is the problem with the Thurmond Amendment: while it was added ostensibly so landlords could “protect other tenants,” it actually works directly against public safety interests. Securing safe, stable housing is one of the greatest challenges for people during reentry, and it makes a difference in reentry success, as previous research has shown. Creating additional barriers to housing for people with criminal records is simply bad policy.

To learn more about the effort to repeal the Thurmond Amendment, go to https://www.thurmondamendment.org.

Footnotes

  1. Drug distribution/manufacturing charges are typically felonies, but some states classify certain distribution/manufacturing charges as misdemeanors, such as when they involve marijuana. The Thurmond Amendment also excludes people with these misdemeanor convictions from fair housing protections.  ↩

  2. For the years 2007-2023, for which our state court estimates are based on arrests for drug sale/manufacturing and the proportion of those arrests that result in felony convictions, we did not attempt to disentangle arrests that might have resulted in federal court convictions. However, we believe that this likely results in an undercount of felony convictions rather than double-counting, because arrests by the Drug Enforcement Agency (DEA) — the federal agency that makes the most drug arrests .— are not reported to the FBI’s Uniform Crime Reporting program (our source for arrest data). And because most DEA arrests result in federal rather than state prosecution, the resulting convictions are captured in the federal United States Sentencing Commission conviction data.  ↩

  3. This ratio has varied over the years; in 2004, 71 per 100 arrests for drug sale/manufacturing resulted in felony convictions, and in 1986 it was 41 per 100 arrests.  ↩

  4. The percentage of people convicted of drug “trafficking” who had prior convictions for the same offense increased fairly steadily over the years it was reported, from 27.3% in 2016 to 33.3% in 2023. Because of this linear trend, we considered using estimates based on the least squares regression line for those years, but ultimately decided that those estimates were likely to underestimate the number of people with prior convictions (for example, this method would predict just 5% of people convicted in 1990 had a prior conviction for the same offense). Instead, we opted to use the larger proportion which produced a more conservative final estimate of unique convictions for drug sale/manufacturing.  ↩

  5. For example, we excluded about half of all estimated state court convictions under the assumption that they could all be subsequent convictions for the same offense, even though the data we used to rationalize their exclusion was based on how many people arrested for drug sale/manufacturing had any prior felony conviction, not specifically drug distribution or manufacturing convictions. Given the relatively small proportion of drug sale/manufacturing convictions out of all state felony convictions reported from 1986 to 2009 (an average of 19%), and the fact that more people released from prison sentences for drug offenses are rearrested for non-drug charges than for drug charges, this choice almost certainly excluded many people who did not have a prior conviction for drug sale/manufacturing. Furthermore, our estimates do not include people who have only a misdemeanor-level drug distribution/manufacturing conviction, even though these convictions also bar people from federal fair housing protections under the Thurmond Amendment.  ↩

  6. This is known as the “discriminatory effects rule,” which the Department of Housing and Urban Development (HUD) explains in this helpful Fact Sheet: “The Fair Housing Act bars more than intentionally discriminatory conduct — it also bars policies that have an unjustified discriminatory effect based on race, national origin, disability, or other protected class. As an example, a landlord’s policy of excluding people who have any criminal record… often will have a discriminatory effect based on race, national origin, and disability.” While these policies are not always unlawful, as HUD points out, “a policy that ha[s] a discriminatory effect on a protected class [is] unlawful if it [is] not necessary to achieve a substantial, legitimate, nondiscriminatory interest or if a less discriminatory alternative could also serve that interest.”  ↩

  7. Most of these people (72%) were in prison for drug trafficking (manufacturing or distribution) as opposed to possession (25%) or other drug offenses (3%). See Table 3 in the Bureau of Justice Statistics report Profile of Prison Inmates, 2016.  ↩

  8. These percentages were also high, if less dramatically so, among people in federal prisons whose most serious offense was drug-related: 61% reported using any drug in the month before the arrest that led to their incarceration, and 38% reported using at the time of the offense. See tables 4 and 5 in the Bureau of Justice Statistics report Alcohol and Drug Use and Treatment Reported by Prisoners: Survey of Prison Inmates, 2016.  ↩

  9. On this point it is worth noting that before Sen. Thurmond introduced his amendment, the bill already included language allowing discrimination against people “convicted two or more times … of illegal manufacture or distribution of a controlled substance” (emphasis added). In his rationale for that amendment, Rep. Bob Walker noted that, on the question of whether people who used drugs would be protected under the law, an earlier committee report had made clear that the intent was that “somebody who has cleaned up their act” would not be excluded from protections but that “we are not going to allow current users to have the protection.” Walker saw his amendment (excluding “dealers” with two or more convictions) as an extension of that logic, suggesting that he and other members of Congress — unlike Thurmond — recognized that people change and that they should not be treated differently under the law if they were not “currently engaged” in drug distribution (emphasis added).  ↩


A recent study from a researcher at University of Pennsylvania finds that higher jail rates are associated with higher death rates, especially for Black people and women.

by Emily Widra and Wendy Sawyer, January 30, 2025

The health, social, and economic harms of incarceration extend far beyond the people behind bars to their children, families, and entire communities, as a large body of research has shown. New research from Anneliese Luck at the University of Pennsylvania adds to this evidence, finding strong links between higher county jail incarceration rates and higher county mortality (death) rates. While researchers have already established the clear connections between jail incarceration, community health, and deaths, Luck’s analysis in The Distribution of Carceral Harm: County-level jail incarceration and mortality by race, sex, and age reveals how these connections vary across age, sex, and race. Generally, Luck finds that higher jail rates are associated with higher death rates for Black people and for women than for white people and men — with the notable exception of older Black men, for whom the “mortality penalty” of higher jail rates is most dramatic.

Luck’s analysis of racial differences is a particularly important contribution, given that the burden of incarceration falls disproportionately on Black communities. While Black people make up less than 14% of the U.S. population, they account for 42% of people who are incarcerated; unsurprisingly, Black people are also overrepresented among people with an incarcerated family member. Ultimately, Luck’s breakdown of the relationship between higher jail rates and elevated death rates by demographic characteristics gives us a clearer picture of the carceral system’s disproportionate impacts on the health and well-being of some of the most vulnerable populations.

two line graphs showing that as jail incarceration rates increase, so do county death rates for white men, white women, Black men, and Black women.

Methodology

It may be useful to define some of the terms used in Luck’s study and in this briefing discussing her findings. The main variables of interest are:

  • County-level jail incarceration rates (more simply, “jail rates”): This is the number of people held in a local jail relative to the number of people in the jail’s jurisdiction, which is usually a county (jails are usually run by counties or municipalities). Incarceration rates are typically expressed “per 100,000 residents,” but they can also be calculated for specific groups within the larger population — for instance, Luck uses the number of Black people in a county jail relative to the number of Black people in the county to express the county-level Black jail rate. A higher jail rate indicates that the county incarcerated a larger portion of its population.
  • County-level mortality rates (or “death rates”): This is the number of people in the county who die within a certain time period (in this case, five years), relative to the total number of people in the county. This rate is also expressed “per 100,000 residents” or per 100,000 people who share a certain characteristic, such as race, sex, or age group. A higher mortality rate indicates that a greater portion of its residents died over a certain period of time.
  • Race, age group, and sex: The data used in Luck’s study include two racial categories (non-Hispanic Black and non-Hispanic white), five age groups (19 and younger, 20-34, 35-49, 50-64, and 65+), and two sexes (male and female).

As an additional note on the language used in this briefing, we (like Luck) also use the term “mortality penalty” as a kind of shorthand to describe the increase in death rates associated with increases in jail incarceration rates. While the word “penalty” often implies a causal relationship, it’s important to note that the findings we discuss describe correlations between county jail rates and county death rates, not direct causes and effects.

For data sources, Luck used the race-specific1 jail incarceration rates from the Vera Institute of Justice’s Incarceration Trends database2 for over 1,000 counties across the country.3 She calculated the county-level death rates by combining restricted vital statistics death data from the National Center for Health Statistics with publicly available population estimates from the U.S. Census Bureau by age, sex, race, ethnicity, county, and year; this gave her age-specific death rates by county and year for four groups: Black men, Black women, white men, and white women. She then pooled (merged) the county death rates for 2010-2014 and 2015-2019, which she analyzed in comparison to the 2009 and 2014 jail incarceration rates, respectively.4

In this study, the average jail incarceration rate for Black people across all counties in the sample (1,060 per 100,000 Black residents) is more than four times that of white people (260 per 100,000 white residents) in 2014.5 This is a reflection of the well-documented racial disparities in U.S. incarceration. There is also a much wider range of county jail incarceration rates for Black people than for white people: one standard deviation6 in the race-specific jail rate is 1,500 per 100,000 Black people, but just 400 per 100,000 white people.7 Because of these differences, the findings of this study are expressed differently for Black and white populations.

Luck analyzed the data using two models that each included different variables; both showed strong, statistically significant links between county-level, race-specific jail rates and death rates across both sexes and races, and across almost all age groups. The first model simply looked at the relationship between the county-level, race-specific jail rates and the county-level death rates of the various demographic groups. In the second model, Luck controlled for a number of county-level characteristics like poverty rate, violent crime rate, percent with a college education, urbanicity, and race, age, and sex distributions. This more sophisticated model accounts for factors besides jail rates that could explain the differences in death rates, to try to isolate the relationship between jail rates and death rates as much as possible. In this briefing, we focus on the results of this second model.

Limitations of the study: Some contextual notes on the findings

Like every study, this study has some limitations. Luck relies on existing data gathered for different purposes, so there were some constraints on how she could use the data to assess the relationship between jail incarceration, deaths, and demographics. She explains various data limitations in her publications, but we thought these two were worth noting here:

  1. The sample was limited to counties with large enough Black and white populations to allow for valid comparisons between racial groups. So while the sample represents the majority of the nation’s Black and white residents, it reflects a somewhat more racially diverse and less rural subset of counties than we would see if every single county was included. In order to include as many less-populous and rural counties as possible (375 in the final sample), Luck pooled the mortality data into two five-year periods (instead of looking at just a few deaths in a county in one year, she used the larger number of deaths over a five-year period).
  2. Previous research indicates that the association between jail incarceration rates and community death rates weakens over time: the link is strongest when you compare jail rates to mortality rates a year later, and weaker when you compare them to mortality rates five or ten years later. Because Luck uses mortality data pooled across a five-year period, her analysis likely underestimates the associations she finds in this study.

To be clear, these limitations do not diminish this study’s contribution to a robust body of evidence of the harms of incarceration on entire communities; they simply provide additional context.

Read the entire methodology

 

Key findings from this study

The results of this study support our understanding that policing and criminalization disproportionately impact the same communities that are most vulnerable to any number of negative outcomes, including high unemployment rates, decreased life expectancy, worse health and worse access to healthcare, and exposure to environmental dangers, inevitably contributing to the observed differences in community death rates.8

Race-specific measures reveal more about the link between incarceration and death rates

By incorporating race-specific measures into the analysis, Luck’s new study is able to show how different demographic groups in the same communities fare under aggressive jailing. Importantly, it also demonstrates that using “race-neutral” measures, as most previous studies do, actually underestimates the scale of the “mortality penalty” — that is, the increase in death rates associated with increases in jail rates. To show this, Luck ran her analysis again using total population rates (i.e., not differentiated by race), and found increases in total jail rates were associated with death rate increases of 0.3 to 1% across the various demographic groups she studied. While this is a statistically significant difference, using race-specific measures yielded a much greater difference in death rates (1.4% to 1.9%). As a result, the new study’s use of race-specific data provides a more nuanced look at the people facing the most serious harms associated with jail incarceration.

Higher jail rates are associated with greater increases in death rates for women than men

The new study finds that both Black and white women’s death rates in almost every age group increase more dramatically with higher jail rates than men’s do. An increase of one standard deviation in the white jail rate (400 per 100,000) corresponds to an increase in the death rate by 1.4% for white men and 1.9% for white women of all ages. An increase of one standard deviation in the Black jail rate (1,500 per 100,000) corresponds to an increase in the death rate by 1.8% for Black men and 1.7% for Black women of all ages — but this is driven by a single age group of Black men (65+) for whom the increase in mortality is more than twice that of Black women (65+), as we explain below. For all other age groups, the “mortality penalty” is higher for Black women than Black men. Because men are incarcerated at rates far higher than women,9 the impact of the carceral system on women’s lives is often overlooked, but this research underscores the need to study how mass incarceration endangers women’s lives inside and outside of jails and prisons, too.

two bar charts that show women's mortality rates increase with higher jail rates more than men's for both Black and white women, except for Black people aged 65 and older.

As other research has shown, jail incarceration disproportionately impacts women’s well-being and health in a number of ways. The rising jail rates of women mean that more and more women are directly impacted by the carceral system, and those women are more likely to have medical conditions and face higher jail death rates than men. Indirectly, women are profoundly impacted by the detention and incarceration of family members: 1 in 4 women have had a family member incarcerated. Higher incarceration rates are associated with a host of negative health consequences for non-incarcerated women: increased frequency of adverse reproductive health outcomes, diminished access to healthcare, and elevated rates of new HIV infections. There are also serious financial repercussions for women with incarcerated loved ones which can ultimately have downstream effects on health and mortality.

The one exception: The “mortality penalty” is greatest for Black men 65 and older

The larger increases in women’s death rates that we see with higher jail rates are consistent across all age groups and both races — except among Black people 65 or older. Across counties with higher Black jail rates, the death rates of Black women under 65 were 1% to 3.4% higher (depending on the age group) than in the counties with lower Black jail rates; these are greater differences than observed among Black men under 65 in the same counties. However, for people 65 years or older, this trend was reversed: higher Black jail rates were associated with a 2.1% increase in death rates for Black men over 65, but a smaller 1% increase in death rates for Black women over 65.10 The author explains the implications of this finding:

“The disproportionate toll absorbed by older Black populations—particularly men, and largely driven by coupling of the increasing penalties of jail incarceration with already high levels of mortality—calls attention to the ways racial inequalities in incarceration may exacerbate other forms of socioeconomic, political, social, and health disadvantage that have been historically shouldered by Black individuals in the United States.”

Because Luck’s research is among the first to examine the relationship between jail incarceration and mortality by race, sex, and age, these findings offer new and damning evidence for what we already know: the burdens associated with incarceration are disproportionately carried by those who are already most vulnerable to other socioeconomic disadvantages.

Conclusion

This study contributes to the growing body of evidence that mass incarceration has fatal consequences that extend far beyond jail cells and prison walls. Luck’s use of race-specific jail rates to assess the ways in which jail incarceration affects white men and women differently from Black men and women calls attention to the racially disparate community consequences of incarceration.

Women and older Black men are particularly vulnerable to the “mortality penalty” associated with higher jail incarceration rates, suggesting that jails contribute to the “uneven geography of health and mortality” across the United States. In addition, this research underscores the role jails and short jail stays play in public health. While much research on the association between population-level health outcomes and incarceration has been focused on policing and prisons, these new findings emphasize the need for research to incorporate local jails into our understanding of how the carceral system hurts the health of individuals, families, and communities.

 

Footnotes

  1. “Race-specific” rates are rates calculated for a specific racial group. The race-specific jail incarceration rate is the number of people in jail in a specific racial group relative to the total jurisdiction-wide population of that racial group.  ↩

  2. In its Incarceration Trends dataset, Vera presents jail incarceration rates for counties per every 100,000 residents aged 15-64. Because these jail incarceration rates exclude youth under 15 years and older adults, we can assume they represent at least a slight undercount of the total number of people incarcerated in jail. In 2022, the Bureau of Justice Statistics reported that there were 1,900 people under 18 years old in local jails, but we do not know how many of those youth were under 15 years old. Vera’s Incarceration Trends dataset has been used frequently in studies of mortality and incarceration, including Kajeepeta et al. (2021), Weidner & Schultz (2019), and Nosrati et al. (2021).  ↩

  3. Luck included counties with populations of at least 5,000 people in each race-sex category (Black-male, Black-female, white-male, white-female) in her analysis. Ultimately, the study included 1,103 counties, representing more than 95% of the total U.S. Black population and approximately 76% of the total U.S. white population. Luck explains that while this sample is not entirely nationally representative — for example, the sample reflects a slightly more racially diverse and slightly less rural subset of counties — there are only “marginal” differences between this sample and all counties in the U.S. in terms of mortality, jail incarceration, and the county covariates (county-level poverty rate, violent crime rate, college education, percent of population that is Black, percent of population that is male, percent of population that is aged 20-30, and urbanicity).  ↩

  4. Luck explains that she did this to ensure the temporal ordering of the relationship between jail incarceration rates and the subsequent five-year pooled death rates. Her use of the two time periods (2010-2014 and 2015-2019) offered more stability to her mortality estimates and allowed the inclusion of more counties. For more information on this process, please see the author’s explanation in her Data and Methods section.  ↩

  5. These rates are slightly different from the race-specific jail incarceration rates calculated by the Vera Institute of Justice, which were 944 per 100,000 for Black people and 266 per 100,000 for white people in quarter two of 2014. These rates differ because Luck indirectly estimated the mean (average) incarceration rates based on a weighted average of race-specific jail rates across counties, weighted by the total population.  ↩

  6. The standard deviation is a measure of how much variation there is in a certain measure (like county-level jail rates) within a sample population (like the counties included in a study). Where there is wider variation in the individual data points, the standard deviation is greater, and where there is less variation, the standard deviation is smaller. Standard deviations can be useful to distinguish between observed measures (like county jail rates) that are more typical (closer to the average for the population) versus those that are especially low or high compared to the others in the dataset. That is how Luck uses standard deviations in this study: when she uses “an increase of one standard deviation” to describe a difference in jail rates, you might think of that as “in counties with jail rates well above average for the population” or “in counties with higher jail rates than most.”  ↩

  7. Luck expresses the standard deviations as changes in percentage points, which we reframed as change in incarceration rate: for example, an increase of 0.4 percentage points from an incarceration rate of 1,000 per 100,000 would be 1,400 per 100,000 people, and an increase of 1.5 percentage points from an incarceration rate of 1,000 per 100,000 would be 2,500 per 100,000 people.  ↩

  8. Because of the nature of the data and research included in this study, we cannot necessarily draw causal conclusions about the direct impact incarceration rates have on mortality rates.  ↩

  9. In 2022, men had a national jail incarceration rate of 345 per 100,000 male residents, while women had a jail rate of 55 per 100,000 female residents, according to Table 4 of the Bureau of Justice Statistics report Jail Inmates in 2022 — Statistical Tables.  ↩

  10. This finding adds to what we know from existing research showing that Black men disproportionately experience the serious health implications of incarceration, frequently appearing later in life.  ↩


January 28, 2025

The systems meant to maintain order and safety in prisons are ripe for abuse by corrections staff, are frequently used to dole out extreme punishments, and play a key role in keeping people in prison longer, a new report shows. The Prison Policy Initiative’s report Bad Behavior: How prison disciplinary policies manufacture misconduct, released this morning, offers an overview of all 50 state prison systems’ disciplinary policies, and explains how the use of these policies as a tool for mass punishment works against prisons’ stated goal of rehabilitation.

Bad Behavior is the broadest review of disciplinary policies to date, and draws on original research as well as testimony from 47 currently incarcerated people, providing an essential look at how prisons are run in the age of mass incarceration. The report’s findings help explain why over 50% of people in state prisons in a typical year are punished at least once for misconduct:

  • It is nearly impossible to avoid disciplinary infractions behind bars: Prison rules cover a vast range of possible conduct, including vague conduct such as “disrespect” and redundant rules about rulebreaking, and the vast majority of disciplinary cases are for minor violations rather than interpersonal harm.
  • Incarcerated people have no meaningful way to defend themselves when accused of infractions: Accused people are typically not allowed to seek representation, and face significant obstacles to finding and presenting evidence (including witnesses) at disciplinary hearings, meaning that many people are severely punished based solely on the testimony of a corrections officer.
  • Discipline policies are exacerbating America’s mass incarceration crisis: People found guilty of disciplinary violations are frequently put in solitary confinement or have good-time credits revoked, both of which can effectively lengthen their prison sentences.
A chart showing over half of people in state prisons are written up for disciplinary violationa annually, and most are minor violations with harsh punishments.

The report notes that misconduct records impact incarcerated people’s chances of earning early release in other ways as well, such as by preventing them from participating in educational or job training programs, and working against them in hearings before parole boards.

“Whether it’s being stripped of one’s ability to visit with family, getting expelled from programs, or being put in solitary, punishments for rulebreaking always come with a cost to rehabilitation and reentry,” said report author Brian Nam-Sonenstein. “State lawmakers should be paying close attention to how many minor infractions are punished in prisons, and the impact this has on people’s circumstances when they’re released.”

The report issues recommendations to departments of corrections for how to immediately make their disciplinary systems fairer and more constructive, including:

  • Reduce the number of misconduct rules, focusing first on rules that are redundant and that create opportunities for discrimination and abuse.
  • Limit the influence of misconduct records on early release decisions, recognizing that most infractions are minor and that rules are often enforced arbitrarily.
  • End solitary confinement and bans on family contact, and institute non-punitive responses to violations such as drug use behind bars — especially in facilities where treatment is practically nonexistent.
  • Improve fairness and accountability in disciplinary processes, starting with basic measures such as allowing people representation at hearings and the ability to gather and present evidence and witnesses.

“The disciplinary system behind bars is largely a mirror of the criminal legal system on the outside, with one crucial difference — departments of corrections can modify their systems at any time,” Nam-Sonenstein said. “Immediate action can — and should — be taken to stop people in prisons being thrown in solitary or having their release jeopardized because of a system that is so reactive to minor misbehavior, and often manufactures it out of whole cloth.”

The full report is available at https://www.prisonpolicy.org/reports/discipline.html. Additionally, the Prison Policy Initiative published a guide for reporters investigating disciplinary systems in their state’s prisons, available at https://www.prisonpolicy.org/blog/2025/01/28/discipline-pressguide/.


We offer questions for jumpstarting your reporting, suggestions for finding data, advice for communicating with incarcerated sources, and more.

by Wanda Bertram, January 28, 2025

This week, we released Bad Behavior: How prison disciplinary policies manufacture misconduct, the first 50-state analysis of prison disciplinary systems published in decades. Here, we discuss how journalists can dig deeper into disciplinary policies — a topic that touches many other aspects of life behind bars.

As the report explains, prison misconduct rules cover a vast range of behavior, making these systems ripe for abuse by corrections staff. The four dozen incarcerated people we corresponded with in developing our report described frequent charges for vague offenses like “not standing for count”; harsher punishments for accused people when they attempted to defend themselves against charges; and hearing officers finding people guilty on scant evidence rather than going against the word of another officer.

Our report is a high-level overview of how disciplinary systems work. But for journalists, there is a lot more room to explore how these systems are enforced in practice and how incarcerated people are impacted by the sanctions that follow a guilty plea.

Reporting on disciplinary policies

If you’re interested in investigating the prison disciplinary system in your state, our collection of state disciplinary policy documents should help you get started. Our 2024 briefing on disciplinary fines — covering 16 states where we know those fines are being imposed — might also be useful. We also have more national statistics in our 2022 briefing on discipline.

A good place to start is finding out how many misconduct cases were processed in your state’s prison system in the last 1-2 years. (That will require a public records request, as we explain more below.) The following questions about disciplinary action could also jumpstart your reporting:

  • If your state DOC classifies different violations by severity, in how many recent cases was the most serious charge a minor or moderate one? (You may want to drill down on specific charges, and our report includes a table of common infractions.)
  • How many disciplinary cases processed in recent years resulted in someone being sent to solitary confinement? How many resulted in lost visitation or communication “privileges”?
  • How many days of good time were lost in recent years due to disciplinary action? (We suggest also asking what types of offenses are leading to people having time credits revoked.)
  • How do women, and racial minorities, experience disciplinary action differently? (For instance, our report shows that women are slightly more likely to be written up than men and much more likely to receive “minor” violations.)

In addition to the sanctions imposed when someone is found guilty, misconduct records also carry collateral consequences. You might want to ask these questions to get a better sense of the impact of disciplinary action:

  • Do misconduct records disqualify people in your state’s prisons from participating in any educational, job training, or behavioral programs?
  • What kinds of disciplinary offenses impact parole decisions in your state? Does the parole board ever consider minor violations enough to deny someone early release?
  • Does your state allow prisons to extend someone’s sentence past their original release date due to disciplinary infractions? (For example, in Wisconsin, being found guilty of infractions or being in solitary confinement can both lead to someone’s release being postponed.)

Talking to incarcerated people about disciplinary systems

Incarcerated people are essential sources for reporting on disciplinary policies, and are often eager to share their experiences and views. Be aware, though, that your sources are taking a risk in talking to you. (Ironically, unsanctioned communication with the media may be grounds for disciplinary charges.)

Anytime you’re working with incarcerated sources, setting clear expectations is key. Make sure to communicate the scope of your project and the terms of your conversations with your sources, as well as the risk of retaliation. Be clear about when you are planning to use their quotes and personal information in your story and make plans to protect their identities if necessary. For more guidance, read the Freedom of the Press Foundation’s guide to interviewing incarcerated people.

In talking to incarcerated sources about prison discipline, we suggest asking questions like:

  • Do you feel that the discipline system in your prison is effective at maintaining order and keeping people safe?
  • Are there any conduct rules (or categories of rules) that seem to be enforced more than others?
  • Are people accused of disciplinary infractions in your prison able to meaningfully defend themselves, such as by interviewing witnesses at hearings and presenting evidence?
  • How often are incarcerated people successful in defending themselves from disciplinary charges?
  • How would you change the system, if you could?

We urge journalists to only share biographical information about incarcerated people that pertains to the story. An incarcerated individual’s crime of conviction, for example, might be relevant insofar as it explains how long they have been behind bars. But being judicious about including biographical details will help you build trust with your sources.

Finding data on prison disciplinary systems

The bad news for journalists is that we don’t know how much data departments of corrections maintain about disciplinary action. The good news is that every disciplinary case — whether or not it goes to a hearing — begins with a write-up, and you can file public records requests for these reports and analyze them yourself if necessary.

In some states, the state government is supposed to conduct regular audits or analyses of prison disciplinary systems. The DOC’s official discipline policy should specify whether that is the case. If so, we recommend requesting any reports or audits of the disciplinary system from the last several years.

When requesting copies of actual disciplinary reports, you can ask the DOC to provide only reports from a certain time frame, where a certain charge was filed, where a certain type of penalty was imposed, and so on. If your investigation is looking at trends in prison discipline (rather than the treatment of a specific person), we suggest specifying in your records request that you are not seeking personally-identifiable information, and that the DOC can redact any details that could identify someone. This precaution can preempt records request denials based on privacy concerns.

For general advice on filing public records requests with criminal legal system agencies, check out our records request guide.

Using our report as a resource in other investigations

Disciplinary systems are relevant to many other aspects of the prison experience that journalists may find themselves reporting on. Our report may come in handy if you’re covering:

  • Solitary confinement. As our report notes, 35% of people who reported receiving disciplinary action in a sample year said they were put in solitary confinement as punishment. The section of our report about disciplinary processes dives into how people can end up saddled with punishments like this, with little or no opportunity to defend themselves against the charges.
  • Parole, “good time,” and other early release mechanisms. In nearly all states that use discretionary parole, release rates are declining. As news outlets like AL.com and Cleveland.com have reported, misconduct records play a significant role in release decisions. We also encourage reporters to dig deeper into how disciplinary action affects how much “good time” incarcerated people are able to accrue.
  • Protests and strikes in prison. Disciplinary codes punish several forms of dissent against prison conditions and rules, and in some states, dissenting behaviors like refusing to go to one’s prison job are treated as serious offenses. Our table of common disciplinary offenses helps explain how prison authorities can turn nonviolent protests into punishable infractions.
  • Prison programming. Reporters investigating the availability of educational, job training, or behavioral programs in prisons may want to find out whether misconduct records can exclude someone from participation. While we can’t say for sure, it’s possible that overactive disciplinary systems are effectively barring many people from rehabilitative programs — programs that can be a key part of securing early release.

Discipline systems are administrative processes in prisons that mimic criminal courts, and punishments for infractions are — in the words of corrections officials themselves — “the jail of the prison.” In other words, these systems are a black box within a larger, more well-known black box. Without investigative journalism, it is likely that these systems will remain largely obscure.

If you’re considering writing about prison discipline — or have any questions about our report or this guide — we encourage you to reach out to us through our contact page.


by Leah Wang, December 20, 2024

At the Prison Policy Initiative, we are often cited in academic articles and advocacy materials, but for the first time, we’ve published our own standalone chapter in an academic collection of critical essays and original research. The American Society of Criminology’s (ASC) Division on Corrections and Sentencing, one of several professional groups within ASC, has just published the ninth volume of its Handbook, with a theme of contemporary issues in health and punishment.1 This 800-page behemoth is a goldmine for people interested in how the criminal legal system intersects and interacts with physical, mental, and public health. Our own chapter offers “An Overview of Health and Access to Healthcare for People in State Prisons.”

Many other divisions of ASC publish an academic journal as a contribution to the field, but this division’s Handbook is a unique product that curates the very best in recent scholarship — including critical policy recommendations. The editors of this particular volume also sought insights from people with lived experience, practitioners, policy advocates, and scientists, in addition to the impressive lineup of academic researchers.

Our contribution to this edition of the Handbook is based on our original analysis of a national survey of people in state prisons, summarized in our 2022 report Chronic Punishment: The unmet health needs of people in state prisons. But the chapter goes further than that, explaining how people in prison access healthcare and the barriers they face, and providing an overview of our work on the flawed Medicaid and Medicare policies that exclude and punish system-impacted people. (We are pleased to report that since we wrote the chapter, there have been a few wins for system-impacted people regarding Medicaid and Medicare.)2 We conclude with recommendations to drastically increase access to healthcare services, acknowledge specific areas of need, and above all, move people out of prisons and jails permanently.

The interdisciplinary topics of health and punishment allowed the Handbook’s other authors to showcase their expertise on gender, aging, public health policy, social determinants of health, environmental justice, and more. As a result, the Handbook is an invaluable resource for readers from a wide range of fields, from criminal justice to public health, sociology, medicine, ethics, law, and policy. In the words of Dr. Homer Venters, who wrote one of the Handbook’s closing chapters, this volume offers “a sober understanding of the deep and systemic failures in our national system of mass incarceration.”

We’re delighted to be in the literary company of professors, practitioners, and advocates whose work we admire and rely on as we examine the far-reaching impacts of mass incarceration. You can learn more about the Division or the Handbook here.

Footnotes

  1. Previous volumes of the ASC Division on Correction and Sentencing Handbook have focused on sentencing policy, pretrial justice, and collateral consequences, among other topics. Each volume can be purchased as a hard copy or an e-book from the publisher’s website.  ↩

  2. In November 2024, the federal government approved an important new rule that makes people on community supervision (probation, parole, supervised on bail, or living in a halfway house) eligible to receive Medicare benefits. A year prior, Medicare expanded its enrollment period, undoing the rule requiring incarcerated people to enroll in and pay premiums for Medicare coverage while still incarcerated — a time when they’re excluded from benefits. As for Medicaid, states are increasingly taking advantage of federal 1115 waiver demonstrations, which can provide pre-release Medicaid coverage for people nearing their release from jail or prison (among other expansion efforts).  ↩


Criminal legal system data is important to understanding how the system operates, but it’s highly limited, inaccessible, outdated, and fractured across thousands of jurisdictions. We spotlight some of the most persistent data gaps we came across in 2024.

by Brian Nam-Sonenstein and Wendy Sawyer, December 19, 2024

At the Prison Policy Initiative, we often hear from journalists, advocates, and others looking for basic information about the criminal legal system. Unfortunately, too often we find ourselves unable to help because rudimentary facts about the system are hard to come by: a lot of things are simply not tracked, and the data that do exist are often limited, inaccessibly formatted, fractured across thousands of jurisdictions, and/or severely outdated.

So, this year, we began collecting some of the data gaps we’ve encountered in the course of our work, which we’ve compiled into a Data Wishlist. We’re publishing the wishlist for two reasons: 1) to highlight just how much basic information is missing in the criminal legal space, and 2) to encourage agencies, researchers, and others to compile and publish these data sets and fill these gaps, chipping away at the information black box around so many aspects of mass incarceration. As you will see, many of the gaps identified in our list would answer exceedingly simple questions about the system, how it functions, and who does (and does not) get punished. This list is by no means a comprehensive survey of criminal legal system data gaps, but we hope it helps people understand just how poor the data environment is and encourages people to chase down this information.

Do you have research, or are you planning to do research, that answers any of these questions? Reach out and let us know through our contact page.

Community supervision

Technical violation data

Data we’re looking for: What percentage of all annual arrests are for supervision violations?

Why it matters: We’ve written on several occasions about how technical violations contribute to unnecessary jailing.1 These violations contribute to crowding in jails and prisons, forcing people into traumatizing, burdensome interactions with the criminal legal system for acts that are not technically crimes at all. We know that, at the most recent count, at least 128,000 people were incarcerated for technical violations of probation and parole. While the FBI tracks arrests across many types of crimes, arrests for supervision violations are notably absent. “What proportion of arrests each year are for supervision violations” is an exceedingly basic question that we are sadly unable to answer without these data.

Pretrial supervision data

Data we’re looking for: How many people are under pretrial supervision of any kind?

Why it matters: Pretrial supervision has gained popularity as an ‘alternative to incarceration,’ but we’ve repeatedly covered how it functions as a pipeline to incarceration. This includes pretrial electronic monitoring — a faulty technology that further embeds systemic injustices in communities of color, creates new avenues of harm, and does remarkably little to increase court compliance or public safety. As pretrial supervision spreads across jurisdictions and takes many forms, it’s important that we have a better picture of how many people are being monitored under those various forms and, over time, to see which forms of supervision are becoming more (or less) common, or result in better (or worse) individual outcomes.

Conviction-based public registries and community supervision

Data we’re looking for: How many people are exclusively on registries as a form of supervision?

Why it matters: We’ve previously pointed out how the available data do not allow us to break apart those on registries from those still serving a sentence, making it difficult to get an accurate picture of how many people are being monitored outside of formal community supervision like probation and parole. Given the well-documented harms of registration, the variety of crimes that require registration, and the failures of registration to increase safety, it’s essential that we improve our understanding of the size and scope of this population.

Offense, sentencing, and conviction data

Conviction status for people on electronic monitoring

Data we’re looking for: What are the conviction statuses (e.g., pretrial vs. sentenced) for people on electronic monitoring?

Why it matters: As mentioned above, we’ve covered the problems with looking to electronic monitoring as an “alternative” to incarceration. According to the Vera Institute for Justice, approximately 254,700 adults were under some form of electronic monitoring in 2021, but we don’t know how many people were on electronic monitoring for pretrial supervision or how many were sentenced to it after being convicted of a crime. Currently, these data are spotty and strewn across local and state jurisdictions, which makes it hard to see the full picture of how many people are under surveillance, by whom, and where – and to hold officials accountable.

Offense data, by conviction status and demographics, for people in local jails

Data we’re looking for: What charges are people in local jails being held on? How do they vary by conviction status and demographic characteristics like state of residence, sex, race, and age?

Why it matters: Most people in local jails have not been convicted, but are detained on bail while awaiting trial. Knowing the charges for which they’re being held helps us evaluate how local jurisdictions are using jails, as well as how many people could be safely released. The Bureau of Justice Statistics (BJS) last collected these data at the national level in 2002, which we have had to rely on for the past two decades. The next iteration of that survey is currently underway, but it will likely be at least 2026 before BJS publishes the results. The Jail Data Initiative offers an alternative source for this data, but because jails include different information on their rosters, there are limitations to what we can do with it. The BJS is uniquely positioned to collect this information and should do so more than once every two decades.

Women’s offenses related to intimate partner violence

Data we’re looking for: How many women convicted of homicides committed offenses in the context of intimate partner violence?

Why it matters: We’ve tried to illuminate women’s unique pathways to, and experiences of, incarceration. Some research suggests that significant portions of the population of incarcerated women have been incarcerated for defending themselves against or in response to living with abusive partners. Further research into this area would help us get a handle on how many women convicted of homicides were living in the context of intimate partner violence.

Felony and misdemeanor sentencing by state (and nationally)

Data we’re looking for: What are the mean and/or median felony prison or jail sentences in each state (or nationally)? And what do misdemeanor sentences look like on the state or national level?

Why it matters: National felony sentencing data hasn’t been compiled since at least 2009, and more recent data published by the Bureau of Justice Statistics are based only on people who have been released. Ideally, data on felony sentencing that aren’t limited to carceral sentences (i.e., include probation, fines, or other requirements) would help us get a better sense of trends in felony sentencing. Simply put: we don’t really know, on an aggregate level, how judges are responding to felony convictions. Meanwhile, we know practically nothing about misdemeanor sentencing but would like answers to basic questions, such as how many people are released with “time served” from pretrial detention, how many are incarcerated (and for how long), how many receive intermediate sanctions such as community service or fines, and how many receive community supervision (and for how long)?

Updated sentencing outcomes for convictions internationally

Data we’re looking for: What do sentencing outcomes for convictions look like globally, and how do they compare to those in the United States?

Why it matters: Through our States of Incarceration series, we’ve tried contextualizing the U.S.’s reliance on mass incarceration by comparing it to that of other nations, but data are limited. We could improve this picture if we had up-to-date information on sentencing outcomes in other nations. New data haven’t been released since the early 2000’s.

Good time credit application

Data we’re looking for: At the state level, how have “good time” or earned time sentence credits been applied and how often are they applied incorrectly, leading people to spend more time locked up than they should?

Why it matters: We’ve noted that good time credits are a potentially powerful tool for decarceration and an important mechanism for shortening prison sentences. Misapplied good time is therefore a serious obstacle to release. In this 2023 article from Kentucky, Jason Riley reports that people with good time credits have been held long after their release dates because the credits were misapplied. The underlying data here are from a state audit. This information should be publicly available, and we should have it for every state, but we don’t.

U.S. Marshals conviction and sex data

Data we’re looking for: How many people in U.S. Marshals custody have been convicted, and how does that data break down by sex?

Why it matters: We know tragically little about people in custody of the U.S. Marshals. Currently, we only have the percentage of people in jail who were female and held for the Marshals at the time of the Bureau of Justice Statistics’ 2002 publication of the Survey of Inmates in Local Jails. These data are not just old – they’re also self-reported and therefore not consistent with the more recent administrative data available about people in Marshals’ custody. Additionally, it’s unclear how many people in Marshals’ custody have even been convicted or not. Their website says they house over 63,000 “pre-sentenced” people in various jurisdictions, but the Bureau of Justice Statistics’ 2019 Census of Jails shows a conviction rate of 35% for those held in local jails. We’d like answers to these very simple questions.

Family policing and youth detention data

Referrals by race and ethnicity for the child welfare system

Data we’re looking for: How do referrals to the child welfare system (often referred to by advocates as the family policing system) break down by race/ethnicity?

Why it matters: We’ve written about how the family policing system operates as an extension of the carceral state, but a glaring omission in the available data pertains to the race and ethnicity of children referred to the system. As with all criminal legal system data, this information is crucial to understanding patterns of practice in enforcement — who gets targeted for family policing and who does not?

Youth who are parents in detention

Data we’re looking for: How many youth in juvenile detention are pregnant or have children?

Why it matters: We’ve covered the traumatic consequences of mass incarceration on children and incarcerated parents, and while there’s information on parents in the adult system, we haven’t seen as much on parents in youth confinement. There’s data from the 2003 Survey of Youth in Residential Placement, but it’s extremely outdated. This 2018 article mentions that “approximately one third of female juvenile offenders have ever been pregnant,” and “male adolescents involved with the juvenile justice and foster care systems are also at high risk for getting someone pregnant, with 18% to 31% reporting that they have fathered a child.” But for the most part, we don’t really have any idea of how many kids in youth confinement are also struggling with parenthood while incarcerated.

The flow of youth through confinement facilities

Data we’re looking for: How many youth exit residential placement facilities each year, and how many of them receive aftercare or reentry services?

Why it matters: We’ve written before about how many of the problems plaguing the adult criminal legal system are mirrored in the juvenile justice system. And we know that in the adult context, there aren’t enough reentry services to meet the need – but is the same true for youth? The most recent data we know of were collected in 1999, but much has changed since then. Without the relevant data, it’s difficult to tell how many youth today who are at risk of further criminal legal system involvement are getting the support they need.

Incarceration experience and conditions

Healthcare quality

Data we’re looking for: What is the quality of healthcare in jails and prisons?

Why it matters: While we know that criminalized populations tend to be sicker and have more serious healthcare needs than the general population, we know practically nothing about the quality of healthcare in jails and prisons, other than that it’s bad. Additionally, much of the data we do have lacks the perspectives and experience of the patients: incarcerated people. A basic evaluation of the state of healthcare delivery in jails and prisons is an entry-level need in the corrections space.

Healthcare outcomes in corrections compared to the community

Data we’re looking for: How do healthcare outcomes in prisons and jails compare to the rest of their state?

Why it matters: Similarly, there’s little research available attempting to compare healthcare outcomes in community versus carceral settings. It’s difficult to gauge the extent to which poor healthcare outcomes have to do with the provision of care in punitive settings compared to in the community.

Mortality among states with privatized healthcare

Data we’re looking for: How do mortality rates compare between states with different kinds of healthcare delivery?

Why it matters: While most jails and prisons in the U.S. have privatized medical services, there’s very little research available comparing mortality outcomes between different healthcare delivery models. Having this data could help improve our understanding of whether there’s a distinction between public and private healthcare delivery. This information would be a tiny step forward in evaluating basic outcomes of different correctional healthcare delivery models.

Perspectives of incarcerated people on understaffing

Data we’re looking for: How do incarcerated people experience understaffing? Where do they feel it most acutely, and what do they think should be done about it?

Why it matters: “Understaffing” is the scapegoat for virtually all crises in corrections today, but notoriously absent from analyses are the perspectives of incarcerated people on the subject as well as calls for decarceration as a solution. There have been some efforts to incorporate their perspectives in examining understaffing, but we think there should be much more research and reporting to this end.

Strip search data, broken down by geography and including historical data

Data we’re looking for: How many strip searches are happening in state prisons, and which states do not require tracking this information?

Why it matters: Strip searches are used routinely in jails and prisons, including around visitation, as a general contraband and drug interdiction strategy. These searches have profoundly harmful and counterproductive effects, and create opportunities for acts of sexual violence by corrections officers. Without basic data on strip searches, it’s impossible to know the frequency with which they’re practiced and whether they’re more common in the U.S. compared to other countries.

Economics and financial exploitation

Relative costs for jail, prison, work release, house arrest, probation, and treatment/counseling

Data we’re looking for: What are the costs for incarcerating someone in a jail or prison compared to placement in work release, house arrest, probation, and treatment/counseling, and how do these vary across states or regions?

Why it matters: We have very little sense of how the costs of incarceration compare to things like work release, house arrest, and probation, let alone responses like treatment/counseling or other non-punitive measures. Having this comparative economic data could help shed light on how our society spends money – and what it does (or doesn’t) get in return on that investment.

Jail-level inmate welfare fund data

Data we’re looking for: How many jail jurisdictions have “Inmate Welfare Funds,” and what are their cash balances?

Why it matters: Earlier this year, we published a detailed report on Inmate Welfare Funds (IWFs) – special prison and jail accounts that are funded with money from phone calls, commissary purchases, and other fees. IWFs are intended to benefit the incarcerated population but are often used as slush funds for corrections departments. While we were able to collect IWF policies for all 50 state prison systems, a much heavier lift is to collect and organize these policies for jail systems. Additionally, it would be helpful to have a sense of IWF balances and cash flows in state prison and local jail systems. Having these data would help greatly expand our window into IWFs, how they are designed, how they function, and their exploitative power over incarcerated people and their families.

Pre- and post-incarceration data

Labor force participation for formerly incarcerated people

Data we’re looking for: What percentage of the U.S. labor force is formerly incarcerated?

Why it matters: This past Labor Day, we chronicled ten ways in which mass incarceration is an engine of economic inequality, including using criminalization as a means to discipline and contain labor movements. While we have some data on the experience of trying to obtain work and working after incarceration, we don’t know what proportion of the labor force is made up of formerly incarcerated people. (We would also love to be able to update our research on the unemployment rate of formerly incarcerated individuals, but to our knowledge, no comparable national data have been collected since 2008.)

Updated pre-incarceration incomes of people in prison and jail

Data we’re looking for: How much did incarcerated people earn before they went to prison or jail?

Why it matters: Evidence that incarcerated people are typically much poorer than non-incarcerated people — even before they are arrested — helps show the injustice of a criminal legal system that treats people differently based on their wealth. For example, many people in local jails are there simply because they can’t afford money bail, and people who can’t afford private attorneys may be assigned public defenders with unmanageable caseloads who can’t spend the same time on their cases. Yet the Bureau of Justice Statistics has not published income data since its surveys in 2002 (for jails) and 2004 (for prisons).2 We have had some success using the National Survey of Drug Use and Health to get income data about people recently arrested and booked into jails, as well as people recently on probation and parole, but a more targeted sample of people with current criminal legal system involvement would be better.

Footnotes

  1. Technical violations are behaviors that break probation or parole rules, such as missing curfew, failing a drug test, or missing a check-in meeting; they are not behaviors that would count as “crimes” for someone not under community supervision.  ↩

  2. BJS is currently fielding a survey of people in jails that may include this information, and it attempted to survey people in prison on this question in 2016, but a computer error made those data unusable.  ↩


New Bureau of Justice Statistics data reveal that concerning trends in policing persisted in 2022, even while fewer people interacted with police than in prior years.

by Emily Widra, December 19, 2024

Almost 50 million people reported contact with police in 2022, reflecting the fewest number of police encounters with the public since 2008. But just because the sheer number of police interactions was lower than it has been in decades does not mean the problems with our nation’s fraught system of policing are solved. The newest report from the Bureau of Justice Statistics’ Public-Police Contact series reveals that racial disparities in police interactions, misconduct, and use of force remained pervasive in 2022. In this briefing, we examine the latest data showing that Black people continued to face higher rates of enforcement actions, police misconduct, and use of force despite relatively similar rates of contact with police. These new data also show heightened levels of police interaction and use of force against young adults, and a growing rate of use of force against women, warranting further investigation of trends in policing.

Millions of people contacted police, but mostly not to report crime

Most police contacts are initiated by residents: almost 30 million people initiated contact with police in 2022. However, only half of these people ever reported possible crimes. More often, they were seeking help. Among people who initiated their most recent contact with police, 25% were reporting a non-crime emergency (like a medical emergency or car accident they weren’t involved in), 26% were reporting other non-emergencies (including requests for custody enforcement or other services, accidental 911 calls, asking for directions, and looking for lost pets), and 3% were block watch-related contacts.1

Although we have little national context regarding the reasons for resident-initiated police contact and the outcome of those interactions, a 2022 analysis of over 4 million 911 calls for police service in eight major U.S. cities found that only 4% of calls were related to violent offenses (including gunshot reports); the majority of calls for service did not result in any action related to law enforcement or crime prevention.2 In other words, most calls to the police would be best directed elsewhere if communities had the necessary funding and capacity. Given how dangerous seemingly innocent police interactions can be, this is a sign of the need for community investments and government infrastructure that are better suited to address concerns about quality of life (e.g., noise, animals, or disorderly behavior), health (mental, physical, and behavioral), and vehicle and traffic issues – some of the most common themes of 911 calls for service in the 2022 study.

Traffic stops remain the most common reason for police-initiated contact across all demographics

In 2022, fewer than 1 in 5 U.S. residents over the age of 16 (or 18.5%) had face-to-face contact with police, down from 24% in 2018. The Bureau of Justice Statistics attributes this decline to a decrease in the number of traffic stops,3 which fell by 33% from over 24 million to 16.2 million over this same four-year period.4 Despite this decline, traffic stops were still the most common type of police-initiated contact, regardless of gender, race, or age: more than 12 million drivers5 were stopped by police in 2022, and these stops are often fraught with racial bias and violence.

Racial disparities pervade police encounters

White people were far more likely than Black people, Hispanic people, and Asian people to initiate contact with the police, for reasons including to report possible crimes and emergencies, to participate in block watches, or to seek other kinds of help from police. In fact, 2 out of every 5 (42%) U.S. residents over the age of 16 who had any police contact in 2022 were white people initiating police contact.6

On the other hand, people of color — and Black people in particular — were more likely to experience police-initiated contact, including street stops, traffic stops, and arrests. Forty-five percent of Black and Hispanic people who had any contact with the police were approached by police, compared to 40% or less of white people, Asian people, and people of other races. Not only were Black people disproportionately likely to experience traffic stops and arrests, but they were also more likely to experience enforcement actions7 from police during street stops and traffic stops, and to face police misconduct and use of force:

  • Street stops:8 While the survey found little racial or ethnic difference in the likelihood of being stopped on the street by police, Black people were somewhat more likely9 to face enforcement actions from police in street stops: 18% of Black people stopped received a warning compared to 15% of white people, and 8% of Black people stopped were searched or arrested compared to 6% of white people.10 Hispanic people were far less likely (11%) to receive an enforcement action when stopped than white (24%) or Black people (25%).
bar chart showing black residents are more than twice as likely to be searched or arrested in a traffic stop than other racial groups
  • Traffic stops: Traffic stops are a common site of police violence: according to the 2023 Police Violence Report from Mapping Police Violence, more than 100 police killings (13%) occurred at traffic stops in 2023. The new Bureau of Justice Statistics data show traffic stops continued to be the most common reason for police-initiated contact across all races, but Black people are stopped at higher rates than others: almost two-thirds (62%) of all Black people whose most recent contact with police in 2022 was police-initiated were the driver in a traffic stop compared to 56-59% among all other groups. Black drivers were also searched or arrested at a rate more than double that of other racial groups: 9% of Black drivers were searched or arrested during traffic stops, compared to 4% of Hispanic drivers, 3% of white drivers, and 5% of drivers of other races. In fact, this represents an increase in the proportion of Black people stopped while driving and subsequently searched or arrested by police: in 2020, less than 6% of Black drivers were searched or arrested during a traffic stop. As was the case with street stops, these trends serve as further evidence of racist policing during traffic stops.11
  • Arrests: Black people were more than twice as likely to be searched or arrested during a traffic stop as white people and Hispanic people. This is consistent with total arrest rates reported by law enforcement, which showed Black people were arrested at a rate (4,544 per 100,000) more than double that of white people (2,155 per 100,000) in 2022.12
bar chart showing black residents are far more likely to experience police misconduct than people of other races
  • Police misconduct: Serious racial disparities persisted in the experience of police misconduct. Black people disproportionately experienced police misconduct – defined as the use of slurs, bias, and sexual harassment – in their most recent encounters with police.13 Four percent of Black people experienced misconduct in their most recent police contact – including those who initiated the contact to report crimes, emergencies, or otherwise seek police help – which is six times the proportion of white people who experienced misconduct (0.7%). Hispanic people also experienced police misconduct in their most recent encounter with police at a significantly higher rate – twice the rate of white people.
  • Threat or use of force: In their most recent police encounters,14 Black people were over three times as likely as white people to experience the threat or use of force – defined as threat of force, handcuffing, pushing, grabbing, hitting, kicking, using a weapon or other use of nonfatal force (these data do not include people who died from fatal use of force) – and more than twice as likely to experience police shouting or cursing at them. Since 2020, the proportion of white and Hispanic people experiencing the threat or use of force has actually decreased, while the proportion of Black people experiencing threats or nonfatal use of force has increased slightly. In particular, Black people were more likely to be handcuffed, pushed, grabbed, hit, or kicked, or have a weapon used against them by police in 2022 than they were in 2020. And while they accounted for only 12% of people whose most recent contact was police-initiated or traffic accident-related, Black people represented one-third (32%) of all people reporting threatened or nonfatal use of force in their most recent encounter, and one-quarter (24%) of those reporting shouting or cursing by police.
graph showing racial disparities between percent of people experiencing police-initiated contact and people experiencing threat or use of force by police.

Ultimately, reducing the number of police encounters does mean fewer opportunities for misconduct or use of force, but it has done little to address racism in policing. Black people’s disparate experiences in police encounters that result in searches, arrests, misconduct, or use of force make those encounters more dangerous and deadlier. While information on fatal use of force is not included in this Bureau of Justice Statistics report, we know that Black people are killed by police at a higher rate than other racial groups. The data in this report provide further evidence of the pervasive pattern of racism throughout the criminal legal system.

Police interactions and use of force are most common among young adults

Young adults aged 18-24 years were the most likely age group to experience any police contact at all (25%), including police-initiated contact (15%), and police contact related to a traffic accident (4%). Young adults were also the most likely age group to experience some kind of law enforcement action – a warning, a ticket, a search or arrest – when their most recent police contact was as a driver during a traffic stop (95%) or in a street stop (28%).

While these rates are concerning, what’s most alarming is the rate of use of force against young adults: more than 1 in 5 people (21%) who experienced the threat or use of force in their most recent police encounter were between 16 and 24 years old. Millions of young adults come into contact with police each year, and the consequences of those interactions are serious and can be life-threatening.15 Police contact of any kind is not innocuous: over 70% of police killings in 2023 began with officers responding to a suspected non-violent situation or a case where no crime had been reported, and more than a hundred police killings took place after a traffic stop in 2023. The high rate of police contact among young adults ultimately places them at high risk for dangerous and even fatal consequences.

Disproportionate experiences of use of force among older adults and women

On the other end of the age spectrum, the Bureau of Justice Statistics data reveal a concerning trend among older adults experiencing use of force. While people aged 65 years or older were the least likely adults to experience police contact, they accounted for a growing portion of people experiencing force in police encounters. In 2015, only 0.4% of people who experienced the threat or use of force were 65 or older and by 2022, the proportion of people experiencing use of force that were 65 or older increased more than tenfold to 5%.

bar chart showing growing rate of use of force against women from 1999 to 2022

Although women are just as likely to encounter police as men, more and more women are experiencing use of force over time: 28% of people experiencing the threat or use of force by police in 2022 were women, compared to 13% in 1999. While the new Bureau of Justice Statistics report did not include statistics on women’s perceptions of police force, the 2020 iteration of the report revealed that women (51%) were more likely than men (44%) to perceive the force they experienced as “excessive.” Women with any police contact were also somewhat less likely than men to perceive the police as responding promptly and to be satisfied with the police response.

Conclusion

The Police-Public Contact Survey continues to be one of the few opportunities we have to monitor the big picture of police encounters, but it still falls short of revealing how police actually function in our communities. The current survey does not offer information about the motivations behind police-initiated contact, nor does it provide contextual information behind threatened or nonfatal use of force, such as which type of police contact is most frequently associated with force. Without data broken down by sex or gender and race or ethnicity, we have little insight into the impacts police contact has on women of color, trans people, and other demographics not captured by this dataset. Given these limitations, we are often left pulling details from multiple sources to try to piece together some semblance of an understanding of police encounters in the United States. However, even with those restrictions, this Bureau of Justice Statistics report offers a crucial – and rare – opportunity to assess how and why police interactions are happening and whether the outcomes are safe and appropriate for situations actually requiring police intervention at a national level.

 

Footnotes

  1. Block watch-related contacts refer to police contact within the context of participating in a block or neighborhood watch or other “anti-crime” program.  ↩

  2. For example, in Richmond, Virginia, only 12% of 911 calls for police warranted a police report. In Baltimore, Maryland, over 80% of calls to police were deemed “low-priority” or “non-emergency.”  ↩

  3. Traffic stops are often used as “pretext stops,” where police stop people for minor traffic violations and then use the stop as a catalyst for further investigation. Police have long defended the practice as useful for identifying more serious offenses including drug offenses, human trafficking, and weapons possession, but evidence suggests that while such encounters rarely result in arrests, they are frequently the site of police misconduct and violence.  ↩

  4. The Public-Police Contact Survey from the Bureau of Justice Statistics only offers us the most basic insight into police contact and does not explain the motivations or drivers of police contact. However, data published in the New York Times reveal that the number of traffic stops began declining in 2018 and 2019, and that this decline was subsequently hastened during the COVID-19 pandemic, and has yet to return to pre-2018 levels. The Vera Institute for Justice published an analysis in early 2024 that found many communities that reduced traffic stops in recent years have seen positive results: reduced complaints about police, fewer injuries to police, reduced racial disparities in traffic enforcement, and fewer stops for minor infractions like lighting violations.  ↩

  5. A total of 16.2 million people reported contact with police at traffic stops; more than 12.4 million people were the drivers and 3.8 million people were passengers during these traffic stops.  ↩

  6. It is worth noting that Black and Hispanic respondents to the Bureau of Justice Statistics survey were more likely than white respondents to contact police to report a possible crime or in relation to a block watch, yet they were less likely to report positive perceptions of police responses. In particular, many people who initiated their most recent police encounter (37%) did not think that the police improved the situation; this opinion was most common among Hispanic and “other” racial/ethnic group respondents (42% each). Meanwhile, white respondents gave their police encounters the highest marks across all measures. These differences add to the evidence that police are not serving Black, Hispanic, and other racial and ethnic minority communities as well as they are white communities, despite their arguably greater need, as expressed by residents reporting crime.  ↩

  7. An “enforcement action” is defined as the outcome of the police encounter. Only the most serious enforcement action is counted for those who experienced more than one action. The actions include a warning (the least serious), a ticket, and search or arrest (the most serious).  ↩

  8. In the Public-Police Contact Survey, “street stops” refer to stops by police while in a public place or parked vehicle.  ↩

  9. These differences were not statistically significant at the 90% confidence level, however.  ↩

  10. While the “stop-and-frisk” policies in New York City are particularly notorious for racial profiling, racial disparities in street stops and law enforcement actions occur regularly across the country, including in Washington, D.C., Wisconsin, and California, among many other jurisdictions. In the 2024 annual report of the California Racial and Identity Profiling Advisory Board, stop data reveals that people perceived as Native American had the highest search rates (22%), followed by people perceived as Black (21%). People perceived as white were searched at a rate of 12%, and those perceived as Asian (6%) and Middle Eastern/South Asian (4%) had the lowest search rates of all racial or ethnic categories.  ↩

  11. For example, a 2023 report form the Illinois Department of Transportation found that state-wide, Black and Latino drivers were stopped at rates higher than white drivers, and that in 2023, Black drivers were three times more likely to be stopped a total of two to ten times, and nine times more likely to be stopped more than 10 times compared to white drivers who were stopped.  ↩

  12. We calculated these arrest rates based on Table 15 of the FBI’s 2022 National Incident-Based Reporting System (NIBRS) Tables and the Center for Disease Control’s single-race population estimates for 2022, accessed via the CDC WONDER Online Database and based on U.S. Census Bureau data.  ↩

  13. The Bureau of Justice Statistics report describes instances of sexual harassment by police as “sexual misconduct,” which includes residents “whom police made a sexual comment to, touched in a sexual way, or had any physical contact with that was sexual in nature.”  ↩

  14. The percentages reported by the Bureau of Justice Statistics about use of force and shouting/cursing are among people whose most recent police contact was initiated by police or related to a traffic accident.  ↩

  15. Police contact is associated with increased stress and poor mental health, as well as the potential for traumatization when witnessing police violence. A growing body of research suggests that police exposure is particularly dangerous for Black youth and young adults and can negatively impact their health and well-being. In addition, young Black men aged 25-29 are killed by police at a rate at least three times that of young white men.  ↩




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