Episode 1 - What We Measure Is What We Get: Why Traditional Policing Metrics Are Failing скачать в хорошем качестве

Episode 1 - What We Measure Is What We Get: Why Traditional Policing Metrics Are Failing

In Episode 1 of The Blue Line Project, we take a hard look at traditional policing metrics like clearance rates, arrest counts, and response times—and why they often produce outcomes leaders never intended. These numbers don’t simply describe performance. They shape behavior, incentives, and decision-making at every level of an organization. If we want better outcomes for officers and communities, we have to ask better questions about what success actually looks like—and whether we’re measuring the right things. Sources cited in video: https://www.brookings.edu/articles/re... Judiciary Committee: https://www.judiciary.senate.gov/pres... https://www.washingtonpost.com/dc-md-... Measuring confidence in policing Com stat: https://zencity.io/why-measuring-conf... https://www.police1.com/community-rel.... Study: The "Safety Gap" (Zencity Report, Oct 2025): An analysis found that while crime declined nationwide in 2024, perceptions of safety actually fell. It was only in early 2025 that sentiment began to rebound, showing a significant lag between statistical safety and feeling safe. The report emphasizes that confidence varies heavily by race and income—demographic nuances often invisible in aggregate CompStat maps. Role of Race in policing: https://www.brookings.edu/articles/re... https://counciloncj.org/when-crime-st.... Racial Profiling or bad data: https://www.dolanconsultinggroup.com/... Why you should not trust crime stats as it relates to proving racism or racial bias: https://vincedixonportfolio.com/2024/.... Feedback loops race class and criminal adjudication: https://www.sciencedirect.com/science... Fryer's Roland Fryer's study, titled "An Empirical Analysis of Racial Differences in Police Use of Force" (NBER Working Paper No. 22399, originally July 2016, revised January 2018; later published in the Journal of Political Economy in 2019), uses four distinct datasets to examine racial disparities in police use of force, including non-lethal force and officer-involved shootings (OIS). The core goal is to estimate whether racial differences persist after controlling for contextual factors, suspect behavior, and encounter details. The full paper (including appendices with detailed coding protocols, robustness tables, and variable lists) is available via NBER: https://www.nber.org/papers/w22399 (PDF includes methodology in Sections 2–4 and Appendix B on OIS construction). If you'd like excerpts from specific sections, critiques of the method (e.g., post-treatment bias concerns raised by others), or related visuals/charts from the study, let me know! Heather MacDonald https://www.wsj.com/articles/the-myth...