GJIL researchers at Ryerson University discussed aspects of their research, exploring similarities in their approaches to understanding explanatory journalism.
The three conversations addressed theoretical frameworks, methodological pandemic protocols, and post-pandemic research.
Behind the Numbers of Explanatory Journalism: Bob Clapperton, Charles Davis and Catherine Schryer consider the manifestations of machine learning on audience and content analysis in explanatory journalism.
Explanatory Journalism and Science Communication: Jessica Mudry and John Shiga dig into the numbers and statistics used in journalism, exploring knowledge translation as it relates to numerical literacy.
Alternative Media and Framing Technology: Sibo Chen and Frauke Zeller on the unique methodologies they use to study explanatory journalism, going to to address the challenges and opportunities of knowledge mobilization.