Episode 104: Quantifying the Narrative of Replicable Science

Yoel and Alexa discuss a recent paper that takes a machine learning approach to estimating the replicability of psychology as a discipline. The researchers' investigation begins with a training process, in which an artificial intelligence model identifies ways that textual descriptions differ for studies that pass versus fail manual replication tests. This model is then applied to a set of 14,126 papers published in six well-known psychology journals over the past 20 years, picking up on the textual markers that it now recognizes as signals of replicable findings. In a mysterious twist, these markers remain hidden in the black box of the algorithm. However, the researchers hand-examine a few markers of their own, testing whether things like subfield, author expertise, and media interes