DTLR finds much merit in Wright's arguments. However, I do think referees and editors have to be gatekeepers when it comes to one point that Wright alludes to, but does not emphasize. I and many others have seen methodologically unsound research published, even in prestigious journals with low acceptance rates, in the life and social sciences. A methdological critic would have been able to reject the paper before seeing any of the data. This is a collective failing of authors, referees, and editors, who are often themselves untutored in even basic principles of research design and execution. There has been much discussion of these phenomena, for instance, in a special issue of the Lancet in 2014, and in closely related discussions of reproducible research (for instance). Sadly, that this has continued to be a recognized problem for almost 15 years is a sign of an unhealthy culture of science.
One proposed remedy has much appeal: "Results-Blind Manuscript Evaluation" (RBME), initially proposed by Joseph Locascio over 20 years ago (eg, Locascio, 2019). This involves a two-stage manuscript review, where a mansucript is first evaluated on the basis of the Introduction and Methods sections, without knowledge of the results. Methodologically unsound research can be rejected out of hand at this stage; if not, the manuscript moves to the second stage where its entirety is reviewed, though the decision to accept or reject may still not be based on the results, but only on the soundness of execution, analysis, and presentation thereof. See the cited paper by Locascio for details. RBME would not solve all the problems, but would go a long way in changing the incentives.
DTLR believes that a scientific journal should combine the insights of Wright and Locascio in its efforts to fight publication bias, while ensuring that research with a chance of contributing to, rather than misleading, the work of others, sees the light of day.
References
J. J. Locascio, 2019: The impact of results blind science publishing on statistical consultation and collaboration. The American Statistician, 73 sup 1: 346-351.
J. Wright, 2020: High journal acceptance rates are good for science. Physics Today, 73 (2): 10-11.
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