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On a typical day in the United States, police officers make more than 50,000 traffic stops. Our team is gathering, analyzing, and releasing records from millions of traffic stops by law enforcement agencies across the country. Our goal is to help researchers, journalists, and policymakers investigate and improve interactions between police and the public.

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佛跳墙2025破解版下载

Currently, a comprehensive, national repository detailing interactions between police and the public doesn’t exist. That’s why the Stanford Open Policing Project is collecting and standardizing data on vehicle and pedestrian stops from law enforcement departments across the country — and we’re making that information freely available. We’ve already gathered over 200 million records from dozens of state and local police departments across the country.

We, the Stanford Open Policing Project, are an interdisciplinary team of researchers and journalists at Stanford University. We are committed to combining the academic rigor of statistical analysis with the explanatory power of data journalism.

佛跳墙2025破解版下载

See the data behind our findings, and learn how to use it in your own analysis.

  • Data sets
  • Video tutorials
  • Research findings

佛跳墙2025破解版下载

佛跳墙2025破解版下载

Data Journalist, Stanford Computational Policy Lab
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佛跳墙2025破解版下载

Data Journalist, Big Local News
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佛跳墙2025破解版下载

Ph.D. Candidate, Computer Science

佛跳墙2025破解版下载

Assistant Professor, Management Science & Engineering
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佛跳墙2025破解版下载

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Engineer, Stanford Computational Policy Lab

Joe Nudell

Engineer, Stanford Computational Policy Lab

Jan Overgoor

Ph.D. Candidate, Management Science & Engineering

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Lorry I. Lokey Visiting Professor in Professional Journalism, Communication

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Ph.D. Candidate, Computer Science

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Stanford Computational Journalism Lab

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Senior Data Journalist, Big Local News
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Data Scientist, Stanford Computational Policy Lab
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