I really appreciate the points you make about this system potentially disincentivizing…
Jessica Polka
1

Good point, multiple people have been confused by this.

The relevant comparator group is PIs with exactly 1 R01. Why is this? Two reasons: 1) Most NIH funded PIs have exactly 1 R01. Thus, one R01 is the key benchmark for productivity. 2) The Rule of 21 policy is designed to create more PIs with exactly 1 R01. Thus, the relevant comparisons are PIs with 3, 4, or 5 R01s compared to 1 R01.

Now consider the Rule of 21 policy in light of productivity: based on the Lauer data, the Rule of 21 would clearly worsen NIH investment for productivity by creating more scientists with 1 R01. When one simply looks at the Lauer curve data on a normal linear graph, as discussed, Lauer’s own data show that having a single R01 is about the least productive NIH funding situation, far less productive than 3–5 R01s. Having a single R01 is a very unproductive investment of NIH funds. Essentially the opposition of what was initially claimed. This is also in conflict with the conclusion Collins passed on to congress. As stated by Director Francis Collins in his announcement of the ‘Rule of 21’ on the NIH website, implementation of a GSI limit would “broaden the pool of investigators.” Adding more PIs with a single grant. One of Francis Collins’s first statements on the Rule of 21 in his congressional testimony last Wednesday was, “…above about 3 grants per year it gets pretty flat. That says that those dollars are not giving us as big an impact as if perhaps they were given to somebody who had no grants.” i.e., creating more PIs with a single R01.

Does than mean the NIH should ban single R01s? No, but it shows that the data do not at all support what was claimed. Hopefully Collins can be convinced that what he was initially lead to believe about productivity and the Lauer curve is not actually true, as it applied to at least up to 5 R01, based on values for 1–5 R01s extracted from the Lauer log plot. Having the data available for direct analysis would be much better.

The article has been updated

One clap, two clap, three clap, forty?

By clapping more or less, you can signal to us which stories really stand out.