Dying Behind Bars: Beyond the Data is based off a dataset compiled by the news organization Reuters documenting deaths in U.S. local jails between 2008-2019. Released at the end of 2020, Reuters’ examination of deaths in local jails represents the largest collection and publication of data on inmate mortality conducted outside of the federal government. Reuters estimates that this dataset accounts for roughly 60% of all inmate deaths nationwide. This investigation is important because it highlights the failures of our government on many levels, which we will explore throughout this project as we start to uncover the context in which this dataset sits. And this project only barely begins to scrape the surface.
While Dying Behind Bars is a data visualization project, it is, at its core, a humanistic endeavor meant to illuminate the fact that these are human beings who deserve to be remembered as more than a statistic or data point.
This dataset documents 7,571 deaths in 523 jails throughout the nation during this 12 year period. In California, there were 1,136 deaths in 38 jails. We will be focusing specifically on female jail deaths in California, which is the state with by far the most jail deaths in the country for both men and women. The Reuters dataset documents the deaths of 119 females in 22 CA jails, and these 119 deaths represent 13% of the 909 female jail deaths nationwide.
We can see that CA has by far the most jail deaths of any state:
“Feminist approaches to the understanding of prisons, and indeed the prison-industrial complex, have always insisted that, if we look at imprisoned women, who are a very small percentage, we learn not only about women in prison, but we learn much more about the system as a whole than we would learn if we look exclusively at men.”
–Angela Y. Davis
This project is inspired by the women leading the abolitionist feminism movement who have been working to highlight carceral realities for decades and whose words and ideas are referenced throughout. These women include Angela Y. Davis, Kelly Lytle Hernández, Ruth Wilson Gilmore, Mariame Kaba, Gina Dent, Joanne Barker, and Michelle Alexander.
The project also works from the understanding that carceral punishment and racial capitalism are directly connected; while this is not necessarily the focus here or explicitly evident through the dataset or the visualizations presented, this is the knowledge from which all aspects of this project grew and continues to grow. This project is very much a work in progress.
Dying Behind Bars: Beyond the Data adopts as its guiding light the notion that data is false completeness. Who and what gets erased in data relating to mass incarceration? The project takes up, in its own humble and limited way, the call from historian, scholar, and UCLA professor Kelly Lytle Hernández to think beyond facticity (Hernández, 2021). While data undoubtedly has power, we must also recognize its limitations in conveying the deep damage, harm, and pain perpetuated by a system that continues to benefit from mass incarceration and over-invest in a military police state at the expense of human lives.
Hernández urges us to think about the stories that need to be told as we collectively adopt an abolitionist mindset and take the necessary next steps towards safety and security by making investments that truly have an impact in the wellbeing of communities through secure housing, family support services, and mental health intervention and support to name a few.
Data does have a role in the story, but it is not the whole story.
Hover over the map above to see how many female jail deaths there were for each county throughout the U.S. between 2008-2019.
“Women inside the criminal justice system are often mentioned as an afterthought, if at all. The omission is inexcusable.”
–Michelle Alexander
We have a perverse numbness to the human costs of death in this country, as we also do towards the human costs and realities of carceral punishment. Therefore, deaths in jail sit at the nexus of double numbness and perversity. Add on the fact that, in conversations about jails and prisons, women's experiences are so often excluded.
Women who die in jail are buried under compounding layers of erasure and silence.
There is nothing necessarily “remarkable” about this dataset or the numbers therewithin. While we will dive into and analyze the data to look at how these women are dying, where these women are dying, and who exactly is dying, the bottom line – as we can see from the map above – is that women are dying in jails everywhere.
This knowledge alone – and the data that informs it – might not necessarily stop us in our tracks. This is the very reaction I am hoping to interrogate. What does it say that we might not react when we see seven deaths for a given year? Shouldn't any data point representing lost human lives make us stop?
Isn't one death in a jail one too many?
It is important to understand the complex context in which this data sits; only then can we better understand what it is that the data is telling us and what it fails to tell us. One of the reasons this Reuters data is so important is that it provides vital information that should be collected and made public by our government – but isn’t.
The U.S. Department of Justice has a federal agency, the Bureau of Justice Statistics (BJS), whose job it is to measure and make public data that is related to systems of incarceration and criminalization at the federal, state, and local levels. Wendy Sawyer, Research Director at the Prison Policy Initiative writes, “The Mortality report (formally called Deaths in Custody) are our only ‘official’ source of information about deaths in prison and jail custody; they are essential for holding correctional agencies accountable for preventable deaths” (Sawyer, 2019).
Until the BJS released a report in early 2020, they had not released any data on deaths in U.S. jails since 2013 – and the data in this report only goes up to 2016. Furthermore, the BJS issues national and state-level data (when they actually do release data), but they do not release statistics for individual jails. The Reuters data is the first to provide individual jail death data. The failure to consistently make this information available is a blatant cover-up so these institutions do not need to be held accountable.
Wendy Sawyer and Peter Wagner, Executive Director of the Prison Policy Initiative write: “The various government agencies involved in the justice system collect a lot of critical data, but it is not designed to help policymakers or the public understand what’s going on” (Sawyer, Wagner 2020).
And this was all the case pre-COVID. We can only imagine (or maybe we can't) how the BJS is continuing to abuse their power to conceal the truth about how COVID has impacted inmates’ health. I hope this project helps to shed light on some of the grim realities that COVID has certainly intensified, but have existed for many years.
So this helps us to understand a bit more what this Reuters data does do – it provides necessary information that helps to fill in some egregious gaps.
Before taking a deeper look at some of the specifics that the Reuter's dataset provides for us – along with some of its limitations – we must understand what local jails mean in the process of mass incarceration.
“Jails have become massive warehouses primarily for those too poor to post even low bail or too sick for existing community resources to help. And the burden of jail incarceration doesn’t fall on everyone equally; it disproportionately impacts low-income communities of color.”
–Ram Subramanian
Reuters’ dataset specifically focuses on deaths in U.S. jails. This is really important to focus on because local jails often are left out of conversations about carceral punishment, but they play a critical role as "incarceration’s front door." (Sawyer and Wagner, 2020).
So who is in California county jails? Individuals who are arrested or charged with a state crime are sent to local county jails, and those who can't post bail are kept there while their cases are pending and they await their trials (Grabowicz, 2021). Clearly, the system is especially oppressive towards and exploitative of lower income communities. And as we will see below, most people in CA local jails have not been convicted of any crime.
People who have been convicted of state crimes may remain in local jails or may be sentenced to state prisons, depending on the seriousness of the offense. Lastly, individuals who are charged with federal offenses can also be in county jails while their cases are pending (the federal government contracts with county jails for this purpose) (Grabowicz, 2021).
Every year, more than 600,000 people go to prison.
People go to jail 10.6 million times each year (Sawyer and Wagner, 2020).
While not the focus of this project, we cannot talk about jails without acknowledging the fact that most people in jails have not been convicted.
As Sawyer and Wagner write, "Some have just been arrested and will make bail within hours or days, while many others are too poor to make bail and remain behind bars until their trial. Only a small number have been convicted, and are generally serving misdemeanors sentences under a year. At least 1 in 4 people who go to jail will be arrested again within the same year — often those dealing with poverty, mental illness, and substance use disorders, whose problems only worsen with incarceration" (Sawyer and Wagner, 2020).
Most of the people in jail – and therefore, most of the people dying in jail – have not been convicted of a crime. While this is useful to know and deserving of much more attention than we can give it here (particularly in regards to how this effects rates of suicide in jails), we should remain careful about not using the convicted / unconvicted binary as a way to justify any inhumane indifference or cruel punishment in jails and prisons.
No human being – regardless of their custody status – should be dying behind bars.
“This country’s system of mass imprisonment is devastating the lives of women and is denying them the basic dignity and humanity deserving to all people.”
–Michelle Alexander
When talking specifically about women in jails, it is imperative that we acknowledge the utter failings of these institutions to provide the facilities and basic care necessary for these women to be treated like human begins. Jails are not equipped for women and have not adapted their medical programs, staff, or housing strategies to accommodate their needs (Eisler et al., 2020).
Thousands of women arrive pregnant each year - through examining public records, media reports, and academic research, Reuters estimates that 3-5% of female inmates are pregnant when they arrive in jail (Eisler et al., 2020). There is very little data on this, and there is no national standard for how jails must treat pregnant women.
Many women arriving to jails suffer from mental illness, and jails fail miserably at treating them and their trauma with the care they need and deserve. A 2017 study from the U.S. Bureau of Justice Statistics (using data they collected back in 2011 and 2012) show startling statistics. Among jail inmates, 68% of females had a history of mental health problems (compared to 41% of males). And 32% were in serious psychological distress (compared to 26% of males) (Eisler et al., 2020). More recent data from the BJS has yet to be released. Simply put, jails are not even close to being equipped to meet the imminent needs and trauma of these women with care and respect.
Up until this point, we have focused on the part of the dataset that specifies the numbers of female jail deaths in CA. Now that we have a better understanding of the context within which this dataset sits, we will now start to look more closely at some of the specific attributes that this data includes.
For every death that the Reuters dataset documents, it includes the following information (for many women, not every field was filled in):
– name of the jail and location (state and county)
– inmate’s first & last name
– date of incarceration
– date of death
– cause of death
– date of birth
– race
– gender
– custody status
What are the racial and age breakdowns of these women?
While the above chart might indicate that it is predominately white women who are dying in jail, we should be careful about how we interpret such a chart. Even though there are more white women who died in jail than any other single individual racial category (the classifications of which are problematic and will be further discussed below), more than 50% of these women are women of color.
In trying to keep the humanity and dignity of these women at the forefront, one thread worth exploring is the age at which these women died. I believe this will give us a framework through which we can work to remember these women as women, not as data points.
The “organized abandonment” of mass incarceration leads to “premature death.”
–Ruth Wilson Gilmore
While age wasn't originally included in the dataset, I was able to calculate this given each woman's dates of birth and death (these values were not available for every woman).
The three main causes of death, as they are labeled and categorized within the dataset, are "illness," "suicide," and "acute drugs/alcohol problems." We will come back to these categories a little later on.
There are limitations of this dataset, which aren’t necessarily based on any failings or shortcomings of the Reuters investigation itself, but more having to do with the fact that they are reliant on data that originates in jails and, therefore, is intentionally obscured.
The classification standards by which jails categorize inmates is extremely narrow, limiting, and may not actually reflect these women's realities. This should be considered when looking at any data that may have originated within these institutions. It is also the case that there is often no way to actually know how reliable these classifications within jail data truly are.
Below is a list of some of the limitations of jail-assigned identity classifications as they pertain to – and potentially obscure - this dataset. This information is inspired by the work of Joanne Barker.
--Gender classifications within jail systems are restricted to the female / male binary.
--Racial classifications are based on narrow and racist categories of identity.
Below are the racial categories that are included within this dataset, which are typical within jails and prisons*:
-White
-Black
-Hispanic
-Asian
-American Indian or Alaska Native
-Native Hawaiian or Other Pacific Islander
-Other
*It is imperative to also mention that when more than one race is identified, and one of those is white, that serves as the default. Furthermore, police often assign and report race based on physical assessment (Hernández, 2021).
It is becoming a bit clearer how problematic jail-assigned classifications can be and how they complicate this type of data.
One additional note: while the categories of cause of death were only briefly mentioned earlier and are not the focus of this project, it should be noted that this is yet another area of jail-assigned classifications that is highly problematic and untrustworthy. As was shown in one of the visualizations above, the three main causes of female deaths in jails, as they are labeled and categorized within the dataset, are "illness," "suicide," and "acute drugs/alcohol problems." Jails often withhold the true circumstances and causes of death so they don't have to be held accountable, since many of these deaths are reflections of poor jail conditions (Willmsen and Healy, 2020). And there is little to no oversight ensuring that jails are conducting accurate analyses of deaths within their jails. As David Fathi, director of the ACLU National Prison Project, says, “Jails are perhaps the least accountable part of government in the United States. When you combine that lack of transparency — that lack of oversight — with a marginalized, unpopular captive population, it's a recipe for neglect and mistreatment” (Willmsen and Healy, 2020).
And this was all the case pre-COVID.
“Collectively, our nation has turned away with cruel indifference, leaving the millions of people behind bars both out of sight and out of mind.”
–Michelle Alexander
From doing a lot of reading and research on this topic, I thought the angle that might be most impactful was to somehow incorporate each woman’s first names and their ages into a data visualization. I was inspired by a really impressive visualization that Dr. Posner sent me that displays the "stolen years" of individuals who died from gun shootings in the U.S. (it was created by Periscopic and you can check it out here). Throughout this project, I have also been continually inspired by Ruth Wilson Gilmore's words describing mass incarceration as "organized abandonment" and "premature death" (Gilmore, 2007).
Since I had the birthdates of these women and the dates they died, I was able to calculate each woman’s age - as we've seen visualized throughout this project. I wanted to take it one step further, and based off of data I found on life expectancy adjusted for race and sex (which I got from the U.S. Department of Health and Human Services and the CDC), I then calculated estimates of the lost years for each of these women.
Please spend some time with each of these women's names.
The lost years on the y-axis of these charts reflect the cumulative sum of lost years for these women by year.
And here are the cumulative lost years by CA county.
Click play on this animated map and chart to watch how the cumulative lost years increase for each county by year.
here are the names of these Women:
Alba
Alecia
Alice
Amy
Angela I.
Angela Z.
Anna M.
Anna W.
Antionette
Ariana D.
Ariana M.
Barbara
Betty
Breanna
Chantel
Christina L.
Christina P.
Christina T.
Christine Ann
Christine B.
Cynthia B.
Cynthia D.
Dana
Danielle
Debbie
Denise
Diana M.
Diana P.
Elba
Elisa
Elizabeth C.
Elizabeth M.
Ellen
Eydie
Georgia
Gloria
Heidi
Jacqueline
Janet
Jenna
Jennifer
Jenny
Joanna
Julie
Karin
Karla
Katherine
Kimberly
Kristen
Kristie
Lakaiya
Lashawn
Lashonda
Lavella
Lavon
Lilia
Linda
Linda
Lorena
Lorna
Margaret
Maria B.
Maria G.
Marion
Mary A.
Mary D.
Mary P.
Megan
Michelle G.
Michelle M.
Mindy
Morganne
Morrissey
Muriel
Natalie
Ngoc B.
Ngoc N.
Nicole
Noriko
Olga
Pamela
Patricia
Patsy
Paul
Perla
Priscilla
Qiongxian
Rachel
Ramona
Rhonda
Rose
Ruth
Sandra C.
Sandra V.
Sara
Sarah
Seneta
Shameka
Shandye
Sharon D.
Sharon P.
Shikiira
Silvia
Sofia
Stephanie
Stormy
Susan
Sylvia O.
Sylvia R.
Tammy
Tanyia
Tara
Teresa G.
Teresa H.
Unique
Unnamed
Unnamed
Vanita
Vannett
Within the Reuters data, the total lost years for women who died in CA jails is 4,472.
If that is 60% of the actual number of jail deaths, then the number of lost years is closer to 7,500.
And that is just in California.
If CA represents 13% of the total deaths nationwide, then between 2008-2019, the total number of lost years for women who died in jail throughout the country is around 57,700 years.
–angus fletcher from "The Dictionary of Dark Matters" by the School for Poetic Computation
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