Yesterday the Atlantic published an exceptionally helpful piece in the Science section by Robinson Meyer and Alexis C. Madrigal that offers some excellent explanation of why the nation has dropped the data ball for this pandemic. It's a good read from that perspective. But for education folks, there's more.
In the body of the article, Meyer and Madrigal share some observations about data, and the problems with data-driven anything; these points are important, and should be emblazoned on the office door of every data-driven follow-the-science policy maker and administrator in the country.
1. All data are created; data never simply exist.Before March 2020, the country had no shortage of pandemic-preparation plans. Many stressed the importance of data-driven decision making. Yet these plans largely assumed that detailed and reliable data would simply … exist. They were less concerned with how those data would actually be made.
|Here come the data|
Data are just a bunch of qualitative conclusions arranged in a countable way.
Data-driven thinking isn’t necessarily more accurate than other forms of reasoning, and if you do not understand how data are made, their seams and scars, they might even be more likely to mislead you.