Day: February 19, 2017

The Laws of Credit Dynamics

The (faux) field of credit dynamics studies the motion of intellectual attribution in scientific collaborations.

The first and second laws of credit dynamics are:

1) A vast majority of readers mentally attribute each research paper to just one of the authors in the author list.

2) The attribution of a scientific paper always flows toward the most famous author in the author list, regardless of who actually conceptualized or did the work, or where the best-known author is in the author list.  

Corollary 1:

Even though you, as a graduate student or postdoc, did all the work and are first author, everyone likely thinks the paper is your advisor’s intellectual baby anyway.

Corollary 2 (lies at the intersection between the field of credit dynamics and the field of patriarchal bull$hit studies):

If the case of similar seniority and fame, the credit will always flow towards the male and away from the female scientist. A sizable offset in seniority and fame has to exist in favor of the female over the male contributor in order for the community to start attributing the work to her and not him. 


From Corollary 1 follows that, when you are a brand new assistant professor and you write your first few grants, those grants cannot be proposing trivial extensions of the work you did in your PhD or postdoc group. Why?

First, those papers are not really your papers. They are mentally attributed to your famous PhD/postdoc advisor, even if you feel ownership of them 100%. You have to come up with something that will be your niche, not the next 3-4 papers that you would have done had you stayed there for an even longer postdoc.

Second, I have seen many junior faculty spend tremendous amounts of time writing many, many grants that will all get dinged in review as too incremental, because the proposed work looks like it could just as well be done in the PI’s former lab, and much faster anyway.

The following seem to be some of the biggest issues people face when they become PIs, especially if they trained in famous labs:

a) The new PIs overestimate how highly they are really regarded once they are no longer basking in the glow of the advisor’s big name.

b) They overestimate how much they can do with their own startup package, a brand new lab, and brand new students while, honestly, not knowing yet how to really do the PI job, because all they know is a flush, well-equipped lab, full of experienced people and working like a well-oiled machine.

c) They view the work the same way they did as postdocs, looking at the next several experiments and a handful of papers, rather than realizing that their job is to develop an entirely new research program for the next decade or so, and with an often modest initial budget.

When you are a new PI, with untrained graduate students and limited resources, you have to think much harder and smarter than before. You have to think at least 5 nontrivial steps beyond the obvious extensions of your PhD/postdoc work. You have to develop a unique style in picking interesting problems to work on. The problems you choose to work on better not be of the low-hanging-fruit variety, because with a group that’s both untrained and small, you are unlikely to get to the easy pickings first.

I am midcareer and I still revel in identifying a hard, perhaps long-standing open problem and solving it by relying on my group’s unique expertise, much more so than I care for being yet another participant in the latest fad. While the latter yields more citations in the shorter term, the former warms my heart and is, I believe, ultimately a much better justification for me having a place in science at all.