Feynman and the NIH Initiative to Enhance Rigor and Reproducibility

As one way to crack down on the problem of irreproducible research, the NIH has just announced new...and way overdue... guidelines for research applications.

Rigor and reproducibility will be a key issue in grant reviews beginning with the Jan 2016 applicaiton deadlines. These guidelines call for enhanced attention to the issues of rigor and reproducibility in every facet of the grant application, from literature cited, to the published and unpublished preliminary data that underlie the application, to the proposed experiments themselves.

Despite the announcement's brevity, if you're still too busy to read it all, here's the cliff notes version: Conducting research in an unbiased way happens when the scientific method is used the way it was designed to be used. This is not really all that complicated.

For those who might have forgotten (or never learned) the scientific method, I always recommend Feynman as a primer.

Essay on the Fallability of Data

If I were an editor of The Atlantic, I might have entitled this, "Your Data Probably Don't Mean What You Think They Mean."

From Thomas Levenson:

Reality imposes a final and authoritative judgment on the rights and wrongs of any idea. In the moment, though, each moment, including ours, meaning in science emerges painfully, slowly, one fallible, historically contingent, self-deceiving and (very) occasionally triumphant scientist at a time.