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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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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.

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

  • Data sets
  • Video tutorials
  • Research findings

CatCloud永久免- 优途加速器官网

CatCloud永久免- 优途加速器官网

Data Journalist, Stanford Computational Policy Lab
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Data Journalist, Big Local News
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Ph.D. Candidate, Computer Science

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Assistant Professor, Management Science & Engineering
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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

Vignesh Ramachandran

Stanford Computational Journalism Lab

Eric Sagara

Senior Data Journalist, Big Local News
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Amy Shoemaker

Data Scientist, Stanford Computational Policy Lab
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Assistant Professor, Applied Statistics, Social Science, and Humanities at New York University
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