“The Elasticity of Science”, 2020-10-01 (; backlinks; similar):
This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources.
Data from the National Institutes of Health (NIH) are used to estimate how scientists respond to targeted funding opportunities.
Inducing a scientist to change their direction by a small amount—to work on marginally different topics—requires a substantial amount of funding in expectation. The switching costs of science are large. The productivity of grants is also estimated, and it appears the additional costs of targeted research may be more than offset by more productive scientists pursuing these grants.
[Matt Clancy summary:
“One approach [to building a new field] is to just pay people to work on the topic. Capitalism!
The trouble is, this kind of approach can be expensive. To estimate just how expensive, 2020 looks at the cost of inducing life scientists to apply for grants they would not normally apply for. His research context is the NIH, the US’ biggest funder of biomedical science. Normally, scientists seek NIH Funding by proposing their own research ideas. But sometimes the NIH wants researchers to work on some kind of specific project, and in those cases it uses a “request for applications” grant. Myers wants to see how big those grants need to be to induce people to change their research topics to fit the NIH’s preferences.
Myers has data on all NIH “request for applications” (RFA) grant applications 2002–7200915ya, as well as the publication history of every applicant. RFA grants are ones where NIH solicits proposals related to a prespecified kind of research, instead of letting investigators propose their own topics (which is the bulk of what NIH does). Myers tries to measure how much of a stretch it is for a scientist to do research related to the RFA by measuring the similarity of the text between the RFA description and the abstract of each scientist’s most similar previously published article (more similar texts contain more of the same uncommon words). When we line up scientists left to right from least to most similar to a given RFA, we can see the probability they apply for the grant is higher the more similar they are.
…The interesting thing Myers does is combine all this information to estimate a tradeoff. How much do you need to increase the size of the grant in order to get someone with less similarity to apply for the grant at the same rate as someone with higher similarity? In other words, how much does it cost to get someone to change their research focus?
This is a tricky problem for a couple reasons. First, you have to think about where these RFAs come from in the first place. For example, if some new disease attracts a lot of attention from both NIH administrators and scientists, maybe the scientists would have been eager to work on the topic anyway. That would overstate the willingness of scientists to change their research for grant funding, since they might not be willing to change absent this new and interesting disease. Another important nuance is that bigger funds attract more applicants, which lowers the probability any one of them wins. That would tend to understate the willingness of scientists to change their research for more funding. For instance, if the value of a grant increases 10×, but the number of applicants increases 5×, then the effective increase in the expected-value of the grant has only doubled (I win only a fifth as often, but when I do I get 10× as much). Myers provides some evidence that the first concern is not really an issue and explicitly models the second one.
The upshot of all this work is that it’s quite expensive to get researchers to change their research focus. In general, Myers estimates getting one more scientist to apply (ie. getting one whose research is typically more dissimilar than any of the current applicants, but more similar than those who didn’t apply) requires increasing the size of the grant by 40% or nearly half a million dollars over the life of a grant!”]
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