Off Year Questions with Ariel Edwards-Levy
Manage episode 489490204 series 3609722
After a brief break, Cross Tabs returns with a must-hear conversation between host Farrah Bostic and journalist-pollster Ariel Edwards-Levy, CNN’s Editor of Polling and Election Analytics. Ariel shares insights from over a decade of political polling and reporting, shedding light on how polls get designed, interpreted, and communicated—and why public opinion is more nuanced, contradictory, and dynamic than we often assume.
📌 Topic Highlights
- How polling serves as a form of large-scale journalism
- Question design, framing effects, and the limits of hypothetical polling
- Expressive responding and partisanship’s effect on perception
- The challenge of polling on emerging topics like AI and crypto
- Why polls often fail to capture what people mean when they talk about democracy, education, or trust in government
- What polling reveals—and obscures—about voter discontent with both parties
👤 About Our Guest
Ariel Edwards-Levy is the Editor of Polling and Election Analytics at CNN. Previously, she was a senior reporter and polling editor at HuffPost. She is a member of the American Association for Public Opinion Research and was awarded the 2019 Carey McWilliams Award by the American Political Science Association for her journalistic contributions to understanding politics. You can follow her work (and jokes!) on Bluesky.
🔗 Mentioned Resources
- CNN Polling Hub: https://www.cnn.com/politics/polling-center
- CNN/SSRS polling report: "A record share of Americans want the government to get more done": https://www.cnn.com/2024/05/08/politics/poll-government-done-party-trust
- The Breakthrough Project (CNN, Georgetown, Michigan, SSRS, Verasight): https://breakthrough.cnn.com
- Pew Research on AI: https://www.pewresearch.org/short-reads/2023/08/28/how-the-us-public-and-experts-view-artificial-intelligence
- Roper Center for Public Opinion Archives: https://ropercenter.cornell.edu
- Brian Schaffner’s research on expressive responding: https://sites.tufts.edu/brianschaffner/publications/
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46 episodes