The Kim Foxx Effect

Category: Best data-driven reporting (small and large newsrooms)

Country/area: United States

Organisation: The Pudding, The Marshall Project, The Chicago Reader

Organisation size: Small

Publication date: 24/10/2019

Credit: Matt Daniels

Project description:

This project provides the first detailed look at the more than 35,000 cases that flow through Cook County Prosector Kim Foxx’s office every year. We found that since she took office she turned away more than 5,000 cases that would have been pursued by previous State’s Attorney Anita Alvarez, mostly by declining to prosecute low-level shoplifting and drug offenses and by diverting more cases to alternative treatment programs.

Impact reached:

The project was widely shared throughout the social justice community (the ACLU and Deray McKesson tweeted it). The piece reached the target audience and proved that data journalism can be a catalyst for action and polocy change.

Techniques/technologies used:

We began this project with a simple question: what is the human impact of electing a prosecutor who runs on reform? To try to assess this, we focused on two measures—charges and dismissals—that we can examine through the unprecedented case-level data published regularly by the Cook County State’s Attorney’s Office.

The data was analyzed using both R and Python. The front-end was built using HTML/CSS, Javascript, and D3.js.

What was the hardest part of this project?

The hardest part of this project was making sure that our data work was backed up by reporting. When analyzing a data set about people, you want to make sure you treat it with rigor and respect and not lose sight of the fact that there are people behind the numbers. Since this was the first detailed analysis of this data, we had to get it right. We had several experts check the data work and methodology and partnered with topic and local experts like the Marshall Project and The Chicago Reporter to co-publish.

What can others learn from this project?

  1. There are robust stories to be told with public data.
  2. Go in with a clear driving question and rely on the expertise of others to inform your reporting.
  3. Clearly communicate the data caveats and shortcomings.

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