Prompted by President Obama’s recent order to review the Defense Department’s supplying equipment to local law enforcement agencies in the wake of its use in Ferguson, NPR received Pentagon data documenting every item sent to local law enforcement over eight years. The outlet then posted a cleaned-up version of the data set online along with preliminary takeaways: What exactly the Pentagon distributed and how much the equipment is worth. Though the analyses are smart, NPR admirably admits the data’s limits: it doesn’t tell the whole story about how the program was used with respect to illegal drugs and terrorism, two national public safety concerns the program intended to combat. “The data do not confirm whether either of those public safety goals are, in fact, driving decisions about the distribution of equipment,” according to the initial story. It ends with the following call to action to member stations:
The data are merely a starting point for further exploration into why certain overstocked and surplus items are — and aren’t — being requested. Questions remain about how and why they are being used, and the benefit, if any, to local law enforcement.
NPR gets a LAUREL for its recognition that the data doesn’t provide all the answers yet and for its insistence that the organization (and its member stations) continue the necessary analysis to find them.
While NPR’s piece conceded that its DOD statistics don’t necessarily tell the whole story yet, a FiveThirtyEight piece by statistician Kaiser Fung entitled “How Data Made Me A Believer in New York City’s Restaurant Grades” claims to come to a conclusion—but it doesn’t really say anything. Instead, the piece suffers from a problem that’s prevalent in weak data journalism stories in which authors devises their own sometimes unnecessary methods when a simple approach will do. In his piece, Fung looks at restaurant inspection data in three ways: correlating the types of vermin a restaurant has with its letter grade; examining how certain broad factors may correlate with grades; and charting how over time restaurants have been getting better grades. These are three different ways of parsing the same data, but none of these analyses are pushed far enough to argue convincingly that the inspections work. Fung would have had more success if he zeroed in on one of his approaches. Why do the spectrum of vermin correlate to restaurant grades? Why have grades been improving? Fung clearly knows how to do proper analysis—he is a statistician, after all—but it doesn’t translate here into good journalism. A deeper, focused look at the data, rather than simply slicing it in disparate ways, would’ve kept Fung’s analysis from getting a DART.
Last week, the Urban Institute produced a series of interactive maps exploring school segregation across American counties. The feature was smartly organized, not just in how it presented the graphics but also in explaining them—the maps were accompanied by analyses from journalists, including The Washington Post’s Emily Badger, who explores differences between regions and various urban areas. For example, Badger notes how children living in diverse counties, such as Montgomery County in Maryland, may not attend diverse schools. She also acknowledges some of the data’s shortcomings, namely it doesn’t account for income. Badger and the Urban Institute get a LAUREL for adding context to data and a visualization that are already pretty informative.
Another week out from Michael Brown’s death in Ferguson brought another mesmerizing graphic about racial disparities in police departments in relation to the communities they serve. We applauded a take by The Washington Post a few weeks back and this week are impressed by what The New York Times interactive team did, displaying data by dissecting several metropolitan areas.
These visualizations all are on the whole fascinating, but now it’s time to actually analyze why the race gap exists in so many cities. We’re sure someone is working on this story somewhere and the Times graphic does hint at some explanations. (For example, the racial gap is less pronounced in New York City because a federal judge ruled the city’s Civil Service exam cannot be used to hire officers.) We’re looking forward to the fuller answers that may come with such a story.