How do you manage to do a podcast on a paper that you so very obviously didn't read beyond the abstract? Granted this is one of the more abused papers by the public, but if you are going to talk about it in depth, you should at least know it wasn't based on actual empirical data.
Ioannidis' paper is very clearly a theoretical modeling paper. He plugs in a bunch of parameters to come to the conclusion that "most published research findings are false", but the parameters are pulled from his ass. His modeling mostly hinges on the R parameter (the likelihood that a hypothesis is correct), but it isn't estimated based on empirical data from research. He just tests various different values.
Here's the table that Ioannidis creates of his parameters. They are all just values he created. They aren't based on any actual empirical data.
Not necessarily a knock against the paper. But people should know what it is based on and the strength of its conclusions. Its recommendations for research are all valid and good, but people way overextend the paper.
This paper makes more sense in regards to Ioannidis' work. His career was spent on strengthening research methods. He helped craft the PRISMA guidelines for meta analysis. The gist of this paper isn't necessarily that most research is known to be false, but rather that a lot of research could be more rigorous, higher powered, and replicable.