Letter - “The Myth of Systemic Police Racism” is full of statistical and journalistic errors

Applying some more skepticism to a recent WSJ Op-ed, because it deserves it.
Sociopolitical
Analysis
Author

Thadryan

Published

July 9, 2020

UPDATE: One of the articles misused in the piece has been retracted, with the authors calling out Mac Donald by name as misusing their work.

UPDATE (07/11/2020): The mysterious quote has been found and unleashed a new error. Brief rundown here, details to follow.

A few weeks ago, I published a video and a summary of some pretty egregious lying with statistics that was published in The Wall Street Journal. I was not the only person to observer this. Since then, authors of one of the studies cited have asked for a retraction, saying they were careless in ways that allowed for misuse of their work. They also call out Heather Mac Donald, the author of the Op-ed, by name.

I’d written an essay-style version of my original critique as well, which follows:

The recent article “The Myth of Systemic Police Racism”[1] contains numerous scientific and journalistic errors that invalidate its core argument and suggest negligence or a desire to mislead the reader.

Firstly, It cites studies about police shootings in isolation to draw conclusions about all policing activities, which is fundamentally unsound. Similarly the author includes a study of shootings by the Philadelphia Police Department. This does not entitle you to make claims about “Police” as an entity - it entitles you to make claims about the Philadelphia Police Department.

One of the papers cited[2], a study by Johnson et al, does not make or support the claim that “Police Racism” is a “myth” - it only deals with shootings. Furthermore, two more recent papers analyzed the results of the Johnson paper. The first found, examining its claim “that their results hold across subgroups of victims”[2]:

“.. an alternative model that focused on young (age 20 y), unarmed male victims that showed no signs of mental health problems and were not suicidal in a county with equal proportions of Black and White citizens… suggested that victims with these characteristics are 13.67 times more likely to be Black than White.”[3]

The other[4] found an issue saying “its approach is mathematically incapable of supporting its central claims” given lack of ability to account for a key probabilistic formula. The authors address this in a correction letter clarifying their intent to state “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”[5]. This is an interesting finding but not in line with the claim made in the op-ed: “no significant evidence of antiblack disparity in the likelihood of being fatally shot by police”[1]. Strangely, the author presents this as a quote but it does not appear in the paper cited.

The authors of the follow-up study brought their findings to light months ago. When I accessed the Johnson paper on June 7th, both papers criticizing it and the correction were linked to in the top of the paper so that readers would see new evidence and place the paper in context; they were published in January. The WSJ piece was published June 2nd.

Puzzlingly, the author cites Roland G. Fryer, Jr. One of his most famous findings[6] includes a dataset in which police shootings show no racial disparity, but he found that nearly all other uses of force did. In particular, Fryer states ”Even when officers report civilians have been compliant and no arrest was made, blacks are 21.2 percent more likely to endure some form of force in an interaction”[7]. The second sentence of his abstract[7] mentions racial disparities - it’s hard to imagine a diligent researcher not knowing about this.

The best defence of the article is that it’s an opinion piece. This is insufficient given the confidence with which the author makes their claim and the severity of the scientific errors they make in defending it. The author employs statistical evidence that has been strongly called into question months ago, or is only obliquely and selectively related to their position. Most unforgivably it cites research that goes against its own position out of negligence or a deliberate effort to deceive. Because the piece presumes to inform the reader using quantitative evidence, it should be held to a higher quantitative standard. Given the importance of the subject at hand and considering the speed at which misinformation spreads, ignoring these issues is irresponsible.

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