By on 12.8.21 in Lessons Learned

As an applied demography group located within a research university, we are always looking for ways to share what we learn with the public and highlight work that takes place within our domain.

Today, we’re kicking off a series of interviews with interesting people from all across North Carolina who frequently use demographic data in their work. If you’d like to nominate someone (or yourself) for this series, please reach out to demography@unc.edu – this is a great way to learn from each other.

Ryan Thornburg, who graciously kicks off our series, is an Associate Professor at the Hussman School of Journalism and Media at the University of North Carolina at Chapel Hill. Before teaching journalism, he worked on national and international news teams at the Washington Post. Now, he teaches students how to work with data and how to create data visualizations that help audiences understand major issues.

What are you working on these days?

I continue to stay interested in local journalism and how data can be used to find hidden stories, help people get relevant and timely information about the communities in which they live and how data and automation can help achieve those goals in an economically efficient manner.

How do you use demographic data in your work? How do your students?

For journalists, demographic data is often the denominator we need to put everything in context. Too many times in public debate and in news reporting we see numbers that stand on their own and the reader is left to decide whether that number is big, small or irrelevant. But numbers only matter in relationship to other numbers. So whatever we’re talking about, news reporters always need to put that in context of the relevant number of people as well as characteristics of those people.

What datasets do you continually come back to for your work? Why?

Well, the Census is the big one. I wish I could say I was more creative than that. That’s often where we get the denominator to help understand whether the numerator is telling us something interesting or seeing differences that are explained almost entirely by the demographic make-up of a community. Datasets that journalists use a lot for the numerators of their stories are datasets that have some event that happens in them — an arrest, a property sale, a political donation, or an environmental measurement.

What is the hardest part about working with demographic data?

Probably the hardest part is just not knowing what is out there. A good reporter just has to have a librarian’s mind for knowing the best place to find data for a specific case. Like I said, I tend to just fall back on Census. And it’s not always formatted like I’d want or it’s not as current as I’d want, or it’s not as granular as I’d want. At the end of the day, it’s really challenging to find a way to get all the appropriate caveats with this data into the story in a way that balances brevity needed to keep reader attention with the precision needed to make sure the story doesn’t leave the readers to draw conclusions that go beyond the limits of what the data can tell us.

If someone wanted to follow in your footsteps, what resources would you recommend?

There is no better place for a young journalist to start than with an organization called Investigative Reporters and Editors. They have incredible resources for reporters interested in using data to find hidden stories. There are also so many great groups of journalists who are helping each other with everything from computer programming to data acquisition to statistical analysis to visualization — two of the best are the News Nerdery group on Slack and the Open News community. And my favorite first stop for Census data is CensusReporter.org.

 


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