Publication bias can distort our picture of scientific evidence. One plausible solution to publication bias is to create a home for work that for, whatever reason, struggles to find a home in a good journal. Would that work? One place to get some evidence on this is to look at our experience with preprint servers.

This podcast is a read through of the (initial version of the) article Publication bias without editors? The case of preprint servers, published on New Things Under the Sun.

Articles mentioned:
Frankel, Alexander, and Maximilian Kasy. Forthcoming. Which Findings Should be Published? American Economic Journal: Microeconomics

Baumann, Alexandra, and Klaus Wohlrabe. 2020. Where have all the working papers gone? Evidence from four major economics working paper series. Scientometrics 124: 2433-2441. https://doi.org/10.1007/s11192-020-03570-x

Larivière, Vincent, Cassidy R. Sugimoto, Benoit Macaluso, Staša Milojević, Blaise Cronin, and Mike Thelwall. 2014. arXiv E-prings and the journal of record: An analysis of roles and relationships. Journal of the Association for Information Science and Technology 65(6): 1157-1169. https://doi.org/10.1002/asi.23044

Tsunoda, Hiroyuki, Yuan Sun, Masaki Nishizawa, Xiaomin Liu, and Kou Amano. 2020. The influence of bioRxiv on PLOS ONE’s peer-review and acceptance time. Proceedings of the Association for Information Science and Technology 57(1) e398. https://doi.org/10.1002/pra2.398

Fanelli, Daniele, Rodrigo Costas, and John P. A. Ioannidis. 2017. Meta-assessment of bias in science. PNAS 114(14): 3714-3719. https://doi.org/10.1073/pnas.1618569114

Franco, Annie, Neil Malhotra, and Gabor Simonovits. 2014. Publication bias in the social sciences: Unlocking the file drawer. Science 345(6203): 1502-1505. https://doi.org/10.1126/science.1255484

Brodeur, Abel, Nikolai Cook, and Anthony Heyes. 2020. Methods Matter: p-hacking and publication bias in causal analysis in economics. American Economic Review 110(11): 3634-60. https://doi.org/10.1257/aer.20190687