Data Sleuthing with Friends, or, Texas: the Great Executioner

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My partner Robert and I, we talk about prisons. We talk a lot about prisoners. We talk about grief and redemption and “the system”. We talk about sentencing and we talk about executions. We talk about these things more than any couple I know. And we talk about these things from two perspectives: the Chaplain and the Analyst.

Recently, I’ve been troubled by the lack of standards for sharing data. The way data is shared almost ensures that there will be errors in interpretation. From the various US Government datasets to Reinhart & Rogoff, the format of the data delivered almost certainly requires us analysts to do horrible things to make the data usable. These things include cutting and pasting and reformatting. And often repeating this activity across multiples tabs in an Excel workbook or across multiple CSV files. It’s a CSV file, just put it all in one. These horrible things would be entirely unnecessary if data were shaped and shared properly. I have some definite opinions on this and will offer my recommendations in a future post. That is a story for another day.

While I was working on that “story for another day” Robert and I were listening to the Planet Money podcast “How Much Should We Trust Economics?” This episode explores how Amherst graduate student Thomas Herndon’s replication of Reinhart & Rogoff’s (R&R) paper “Growth in a Time of Debt” revealed serious errors in data handling and ultimately a different conclusion. R&R’s paper has been has been widely cited (over 500 times) by scholars, used to set international economic policy and was a foundation point in Paul Ryan’s budget proposal. Through replicating R&R’s paper, Herndon identified critical discrepancies in the data: some of data was missing due to a coding error, some data was simply left out, and other data had been summarized in a non-standard way. Herndon argues that after “fixing” R&R’s data errors it’s clear that their conclusions were wrong. And if their conclusions were wrong, then how many struggling countries with high debt to GDP ratio failed to receive much need aid? How many lives were affected?

So, how else are people adversely affected by misused data and faulty conclusions? The Planet Money team reached out to Economist Justin Wolfers of the University of Michigan to understand how frequently these types of errors occur in studies. And it’s astonishing. And here’s where we get back to talking about prisons. Wolfers argues that’s he’s “replicated every single paper in the death penalty literature” and there are errors in some 90% of them. While Wolfers agrees that some of these “errors” are methodological issues debated about in the community in many other cases “people just screwed up the math”. He explains that one such error changed the author’s conclusion from “each execution deters 18 homicides a year” to “each execution causes another 18 homicides a year”. It causes another 18 homicides a year. Each execution.

My partner Robert asked if I would do a little data sleuthing with him and look at what information is available on prisons and the death penalty. He wanted to know if I could visualize with data what he sees and experiences in his work with prisons. Some years ago I took a workshop with Stephen Few, arguably one of the foremost thinkers on design and data visualization best practices, and at the end of the workshop he implored us to go out into the world and to “use our powers for good”. I hope my work with Robert and our ongoing dialog about prisons, about the people who live and work there, about the people who die there, about the lives affected by those in prison helps to lead me down that path. Our conversation begins with this:

  • Between 1977 and 2012 2,637 people have been executed in State prisons in the US
  • That’s an average of 73 people executed per year
  • Texas has executed people at a rate nearly 5x higher than the next two states leading in executions, Virgina and Oklahoma
  • Of our 50 states, only 34 have executed a State prisoner during this time, and only 15 states average more than one execution a year.

Clicky

2 thoughts on “Data Sleuthing with Friends, or, Texas: the Great Executioner

  1. Pingback: Letters to Friends » Data Sleuthing with Friends, or, Texas: the Great Executioner

  2. Robert Drake

    Leigh, your Viz is a powerful portrayal of Texas in Executionary Justice. Unfortunately, the model of the prison system that Texas represents is fast being adopted by the rest of the nation. As someone who goes in and out of San Quentin regularly, and studies the system broadly, I know the history of the system and why Texas execution stats are what they are.
    The American prison system was originally an experiment in institutionalized repentance. In the late 18th century, a collection of reformers wanted to replace the use of pillories, gallows and public stocks with “a benevolent and salutary” institution. The new “penitentiary” would be a “receptacle for criminals” to capitalize on the natural human desire for freedom.1 It would provide the inmate “penitents” a place to be isolated and ponder their lives. The system failed dramatically. It was a place of squalor, disease and recidivism.

    After the Civil War, Texas harbored the retreating slave-owning plantation owners who were unwilling to stop forced labor practices. Texas took heed of the great penitentiaries and, with a will to keep slavery alive in some form and profit from the incarcerated, Texas began a program of imprisoning people of color and other “lawbreakers,” using their labor for privatized contract farming and manufacturing. This turned into an extension of the slave system. The prison system in America is an extension of the Texas prison philosophy, which is itself an extension of the slave-holding practices of antebellum America.

    Here are some disturbing statistics about our prison system for which I’d love to see a Viz analysis: A study by David Baldus found that those persons charged with killing white victims should expect to receive the death penalty eleven times more frequently than those charged with killing black victims.2 Crack cocaine offenses (the drug of choice for the poor user – usually black) are punished 100 times more severely than offenses involving powder cocaine, the drug used by the wealthy (white) cocaine using population. The majority of defendants of crack cocaine charges are black (93% vs 5% white).3 With minimum sentencing laws (Three Strikes) you have a population of the under-privileged populating America’s prisons, AND being executed or given life sentences. In the State of Georgia, like California, 98.4% percent of life sentence prisoners are black.4 Another study conducted by the San Jose Mercury News reviewed 700,000 criminal cases comparing crime and criminal history of the defendants. They found that African Americans are six times more likely than whites to be sent to prison for identical crimes.5

    According to statistics obtained from the Death Penalty Information Center, “almost all capital cases (84%) involve white victims, even though 50% of the murder victims were black” and “in 82% of the cases reviewed, race of the victim was found to influence the likelihood of being charged with capital murder or receiving the death penalty, i.e., those who murder whites were found more likely to be sentenced to death than those who murder blacks.”6 Meanwhile, white-collar crimes that sometimes hurt many thousands at a time usually bring no jail sentence at all, but street crimes involving breaking and entering and a few dollars of loss can bring mandatory life imprisonment.

    “Denied a place in society at large, Jim Crow has moved behind bars.”7 The injustice of slavery and post-slavery has been transferred to the invisible world of American prisons. The New Jim Crow is the American prison system and our sentencing laws and practices. With the rise of for-profit prisons, it is also about profit. There are now as many people working for the US prison system as there are people in the system.

    I’d love to see you do a visualization that incorporates these demographics:
    Education, race and income level of the incarcerated and the executed
    “Red” and “Blue” (political) designation of the governor of the state at the times of the executions.
    Labor and for profit prison corporations’ donations to mandatory sentencing initiatives

    Thank you for your insightful analysis, Leigh. This is a great use of your skill set!
    Robert

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