Data collection intended as feedback requires continuous analysis to avoid backlash.

Evidence

Thus, to make the most of the information agencies collect, it should be understood as data, as records that are neither “good” nor “bad.” Rather, such data can serve as feedback from which to learn and continuously refine an agency’s priorities and practices. Stop data, for example, are a veritable treasure trove of information that can help an agency accomplish its goals more precisely, safely, and equitably. Our research team put forth fifty recommendations to tackle racial disparities and improve police-community relations and, in so doing, we advocated that law enforcement agencies reimagine themselves as “learning institutions—that is, as places that collect and use high-quality data based on the goals and values they share with their communities” (Eberhardt, 2016, p. 40). It should go without saying that, in order to maximize the power of data, it must be analyzed. Collecting data but not putting the information to use is counterproductive and can frustrate community members and other stakeholders (Niles, 2016). — Joseph Avery, Jim Sidanius, Joel Cooper, Gregory Davis, Amanda N., Bias in the Law, 425

Categorization

• XREF: Reframes bias measurement as institutional ‘learning’ rather than accusatory audit — relevant to the reader’s question about framing corrections to avoid backfire.
• DEEPTHINKING: Not top-tier, but the distinction between monitoring-as-accountability vs monitoring-as-learning speaks directly to whether measurement hardens or loosens defensive conviction.
• corroborated: 2 independent passages support this claim — Joseph Avery, Jim Sidanius, Joel Cooper, Gregory Davis, Amanda N., Bias in the Law: A Definitive Look at…, 425