Science problem: study says there is not enough information in methods sections of science articles to replicate

A new study suggests the methods sections in science articles are incomplete, making it very difficult to replicate the studies:

Looking at 238 recently published papers, pulled from five fields of biomedicine, a team of scientists found that they could uniquely identify only 54 percent of the research materials, from lab mice to antibodies, used in the work. The rest disappeared into the terse fuzz and clipped descriptions of the methods section, the journal standard that ostensibly allows any scientist to reproduce a study.

“Our hope would be that 100 percent of materials would be identifiable,” said Nicole A. Vasilevsky, a project manager at Oregon Health & Science University, who led the investigation.

The group quantified a finding already well known to scientists: No one seems to know how to write a proper methods section, especially when different journals have such varied requirements. Those flaws, by extension, may make reproducing a study more difficult, a problem that has prompted, most recently, the journal Nature to impose more rigorous standards for reporting research.

“As researchers, we don’t entirely know what to put into our methods section,” said Shreejoy J. Tripathy, a doctoral student in neurobiology at Carnegie Mellon University, whose laboratory served as a case study for the research team. “You’re supposed to write down everything you need to do. But it’s not exactly clear what we need to write down.”

A new standard could be adopted across journals and subfields: enough information has to be given in the methods section for another scientist to replicate the study. Another advantage of this might be that it pushes authors to try to read their paper from the perspective of outsiders who are looking at the study for the first time.

I wonder how well sociology articles would fare in this analysis. Knowing everything needed for replication can get voluminous or technical, depending on the work that went into collecting the data and then getting it ready for analysis. There are a number of choices along the way that add up.

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