(Over)Sharing Data

This is a reflection on Flippen's "Where Are the Hardest Places to Live in the U.S.?" and Leen, Doig, and Getter's "What Went Wrong," about the aftermath of Hurricane Andrew.

It was interesting to learn from Flippen’s article just how difficult it is to find comparable datasets for nationwide spatial research. Typically, I would assume that a reporter would intentionally omit mention of other valuable data points if they were unable to find them. In this case, Flippen points out the unavailable ‘income mobility’ and ‘environmental quality’ data, writing that they did not cover all the counties in the United States. He does this, perhaps to show the resourcefulness of the researchers in other ways. Namely, he describes how they used disability as a proxy for the number of working-age people who don’t have jobs but are not counted as unemployed.

While Flippen’s research utilizes large-scale publically available datasets, the Leen, Doig, and Getter article explores a far broader range of research and data types (aerial images, archives of inspection reports, political lobbying dollars from builders). Their sensationalist reporting pits contractors against insurance companies against meteorologists. They blame the controversy around what caused the uneven destruction of homes in Florida during Hurricane Andrew on the lack of definitive wind data. How is it possible, in 1992, that they don’t have multiple locations from which to track wind speed? I’m most skeptical about the way in which this article confounds its readers with various types of data; rather than using data to paint a clear picture of what happened, they use it to further complicate the narrative of blame in this unnatural disaster.

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