Uncovering an epidemic: Student journalists and data scientists chronicle Rhode Island’s opioid crisis
For several years, Breton had been thinking about bringing that same data-driven approach to reporting on the opioid epidemic, but she knew the datasets involved would be daunting. Sifting through them would likely require expertise beyond what she or her journalism students could muster. So in early 2020, Breton reached out to Ugur Cetintemel, chair of the Department of Computer Science.
Breton pitched Cetintemel on the idea of a course, cross-listed with the English and computer science departments, that would bring data scientists and journalism students together to tackle the opioid issue. The course would take a year or two to get on the books, but Breton believed there would be plenty of interest.
“He looked at me and he said, ‘Why do we have to wait another year or two to do this?’” Breton said. “‘I’m teaching a class this semester called CS for Social Change.’”
A key component of that class, which Centinemel has offered for the last five years, involves student teams partnering with local organizations to help with technical challenges they face. Students have tackled a range of projects. One team worked with a criminal justice advocacy group called Open Doors on a data platform to study correctional data. Another worked with a nutritionist to develop an app that provides healthy food incentives.
“I told Tracy that I was teaching this class, and that we can have one team of students working with her on this series of stories,” Cetintemel said. “She liked the idea, and that’s how this got started.”
Data and stories
Triedman, a computer science and history concentrator, was one of the five CS for Social Change students who joined the project, working with 12 journalism students in Breton’s Reporting Crime and Justice class. The work involved easily spilled the banks of the semester-long classes. The team ended up working together for nearly two years. Triedman was one of several students who continued working on the project even after he graduated.
The datasets used in the project were often enormous and complex, he said. Data from the DEA, for example, detailed every step of every legal opioid transaction in the U.S. for over a decade — from importation of the opium poppy, to its processing in a pharmaceutical plant, to its sale in a local pharmacy. The dataset was hundreds of gigabytes in size with hundreds-of-millions of rows of information, Triedman said.
“You can’t load that onto any normal computer, let alone open it up in Excel and do the normal filtering you would want to do,” he said. “It takes some specialized skill to work on those datasets and to know which tools to use.”
By sifting through that DEA data, Triedman was able to uncover the outsize role that Coventry’s Rhodes companies played in distributing opioid products nationwide, as well as which pharmacies in Rhode Island were handling and selling the most opioid products.
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