Protesters recreate the chalk body outline from the crime scene of the police shooting of 17-year-old Laquan McDonald. Chicago police officer Jason Van Dyke was convicted of murder for McDonald's death. Max Herman/NurPhoto via Getty Images

Despite new research on police brutality, we still have no idea whether violence toward African Americans is fueled by racial prejudice. That has consequences.

Last September, Manhattan Institute fellow Heather Mac Donald, a longtime foe of police reform, testified before a U.S. congressional committee that the reported “epidemic of racially biased police shootings of black men” is false.

In fact, “if there is a bias in police shootings, it is against white civilians,” she said, citing a recent study released by the prestigious Proceedings of the National Academy of Sciences (PNAS).

Mac Donald’s take on the study was generous. Its authors, University of Maryland psychology professor David Johnson and Michigan State University psychology professor Joseph Cesario, weren’t actually making a point about police bias at all. The study was about identifying the race of police officers involved in fatal shootings and showing whether or not it matched the race of their victims, not shedding light on motive, Johnson told CityLab. But after the study came out, other scientists in the field criticized its methodology, prompting Johnson and Cesario to concede a mistake in the way they characterized the study.

Despite the apology, the study has continued to fuel a long-running debate of great significance as localities grapple with how to improve disproportionate rates of police violence against African Americans: Is police violence towards African Americans mostly explained by cops’ racial prejudice? The short answer is that it’s difficult to arrive at a scientific conclusion, because the data is lacking.

Princeton University politics professors Jonathan Mummolo and Dean Knox were among the academics who criticized the study and questioned the value of knowing the race of police officers involved in fatal shootings at all. In January, they published a letter in PNAS and an op-ed in The Washington Post stating that the Johnson-Cesario study “was based on a logical fallacy and erroneous statistical reasoning, and sheds no light on whether police violence is racially biased.”

To determine whether racist motivations are fueling police shootings, you would need to know the race of the people killed by police in a given department, and also the race of all the people who police shot, but didn’t kill. Perhaps the most difficult datapoint is that you would also need the race of all the people police came in contact with, but did nothing to at all. This cumulative data is called the police encounter rate, and the scientists who have been studying police violence say that it is the most critical yet most elusive data needed to register racial bias.

In explaining why the encounter rates matter in this discussion, Mummolo and Knox offer a thought experiment with an unrealistic but easy-to-follow fact pattern: Let’s say an all-African-American police force encountered 90 black civilians and 10 white civilians in a given week, and among those encounters, the officers shot and killed five African Americans and nine white civilians. Then, imagine a white police force encountered 90 white and 10 black civilians in a week, and also killed nine white people and five black people.

Both departments are responsible for an equal number of lives from both races taken. However, the percentage of lives taken in each race is different when the encounter rates are considered: The black police force shot 5.6 percent of the black civilians and 90 percent of the white civilians they encountered, while the white police force shot 50 percent of the black civilians and 10 percent of the white civilians they encountered.

Viewed through the lens of the thought experiment, one can see why it’s inaccurate to say there is an anti-white bias or any other kind of bias in police shootings, as Mac Donald testified.

“I'm not happy with the way that [Mac Donald] characterized our study,” said Johnson. “She characterized it as if we gave information about bias on the behalf of officers. We’re not trying to make statements about the likelihood of being shot by police officers if you’re black, and we don't have the data to do that.”

But he and Cesario made the mistake of writing in the study’s statement of significance that “White officers are not more likely to shoot minority civilians than non-White officers.” In a response to critics published last August, Johnson and Cesario wrote:

We should have written this sentence more carefully. … What we should have written was a sentence about what we did estimate: As the proportion of White officers in a [fatal officer-involved shooting] increased, a person fatally shot was not more likely to be of a racial minority. This was our mistake, and we appreciate the feedback on this point.

While Johnson says their study was not intended to infer racial bias, Mummolo is concerned that leaving the bias question unresolved has consequences, such as leading policy influencers like Mac Donald to make their own incorrect inferences.

“I don’t know what [Johnson’s study] teaches us,” says Mummolo. “It does not teach us that one [racial] group of officers is more or less likely to shoot, and we all seem to agree on that now. They say there’s this absence of a correlation, but that could mean any number of things. Without the other information and the data that are missing, there’s just no way to say what it means.”

Johnson agreed that having the encounter rates is important, but not for the purposes of his study, and he and Cesario are standing by the utility of the analysis, as seen in their reply to Mummolo’s PNAS letter. What the study tells us if nothing else, said Johnson, is the racial demographics of the police officers involved in fatal shootings, which he says has not been previously accumulated in any nationwide studies on police violence.  

“I want to stress how hard it was to get information about these police officers,” said Johnson. “It took over 1,800 hours requesting information from police, looking at legal cases and legal documents as well as media accounts. We didn’t know any of that before we started on this analysis.”

It’s debatable what simply knowing the race of the officers tells us. In the context of the Black Lives Matter movement, people are concerned with how to eliminate anti-black prejudices, if that’s what is driving cops to be more violent towards black people. And an anti-black bias can come from a cop of any race, including black. According to Phillip A. Goff, president and co-founder of the Center For Policing Equity, the data on officer characteristics are neither unprecedented nor necessary for understanding police violence.  

“Nobody who had done responsible analyses of this would be surprised by that,” said Goff, “because as they admit in their paper, black officers are more likely to be patrolling in black neighborhoods. So of course they’re more likely to shoot black people because of proximity. If that is their only argument, then they are saying, ‘We have nothing novel to say.’”

What they all agree on is that there is too little data collected on police violence—the Calvary hill that almost all studies that attempt to address police brutality and racial bias get crucified on. Mummolo said that it is possible that there are ways for academics to get close to police encounter rates, such as by using traffic camera footage in some instances, or using responses from the Police Public Contact Survey. But these would still fall short of the data needed to draw solid conclusions about race and policing.

“The rigor around the science of racism and discrimination is less than it should be, on all sides, and it reduces science to conversations about ideological entrenchments rather than about novel discoveries about the way that the world is shaped,” said Goff. “That makes us all less well-positioned to improve the world as we find it. We should feel badly about that, and we should do better.”

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