Managing your CV and why pre-print waccaloons should be ignored

February 2, 2016

For whatever reasons I was thinking of at the time I was motivated to twttr this:

What I mean by this is that somewhere on the pile of motivations you have to finish that manuscript off and get it submitted, you should have “keeping your calendar years populated”.

It may not always be a big deal and it certainly pales in comparison to JIF factors, but all else equal you want to maintain a consistent rate of output of papers. Because eventually someone will look at that in either an approving or disapproving way, depending on how your publication record looks to them.

Like it or not, one way that people will consider your consistency over the long haul is by looking at how many papers you have published in each calendar year. Published. Meaning assigned to a print issue that is dated in a particular calendar year. You cannot go back and fill these in when you notice you have let a gap develop.

If you can avoid gaps*, do so. This means that you have to have a little bit of knowledge about the typical timeline from submission of your manuscript for the first time through until the hard publication date is determined. This will vary tremendously from journal to journal and from case to case because you don’t know specifically how many times you are going to have to revise and resubmit.

But you should develop some rough notion of the timeline for your typical journals. Some have long pre-print queues. Some have short ones. Some move rapidly from acceptance to print issue. Some take 18 mo or more. Some journals have priority systems for their pre-print queue and some just go in strict chronological order.

And in this context, you need to realize something very simple and clear. Published is published.

Yes, mmhmm, very nice. Pre-print archives are going to save us all. Well, this nonsense does nothing for the retrospective review of your CV for publication consistency. At present the culture of scientific career evaluation in the biomedical disciplines does not pay attention to pre-print archives. It doesn’t really even respect the date of first appearance online in a pre-publication journal queue. If your work goes up in 2016 but never makes it to a print article until 2017, history will cite it as 2017.

*Obviously it happens sometimes. We can’t always dictate the pace of everything in terms of results, funding, trainee life-cycles, personal circumstances and whatnot. I’m just saying you should try to keep as consistent as possible. Keep the gaps as short as possible and try to look like you are compensating. An unusually high number of pubs following a gap year goes a long way, for example.

17 Responses to “Managing your CV and why pre-print waccaloons should be ignored”

  1. Jonathan Badger Says:

    Who exactly are you thinking is reading your CV and looking for gaps? I get that grad students looking for postdoc positions and postdocs looking for jobs need to have the best-looking CV possible, but are you imaging that a grant reviewer is pouring over your CV and saying “Drugmonkey didn’t publish many papers in 2014 as he did in 2013 and 2015?”


  2. Didn’t publish as many papers in 2014 will probably not be noticed. Published zero papers might be.


  3. Juan Lopez Says:

    “An unusually high number of pubs following a gap year goes a long way, for example.”
    I don’t know about this one. There’s a funny effect at play:
    Look at Web of Science or other systems that make a histogram of publications for each year. These are scaled to the year with max productivity. So a highly productive year causes all other years to look worse, and your productivity to look uneven.

    yes, I know people who do look at these plots.

    In my experience, most important is to not have years with unusually low productivity and to have a trend that looks like it’s going up.


  4. E-rook Says:

    Who exactly are you thinking is reading your CV and looking for gaps? I get that grad students looking for postdoc positions and postdocs looking for jobs need to have the best-looking CV possible

    Promotion & tenure committees, new institutions you might apply to, NIH study sections, award committees for your society-of-interest. The highest quality grad students and post-docs looking for a place to launch are also looking at this. Two way street, that is.


  5. drugmonkey Says:

    JB- of course they are. Also, what E-rook said.


  6. New PI Says:

    This advice already sounds outdated to me. I’m in a more computational subfield. I think many of us track preprint dates.


  7. Dusanbe Says:

    The automobile is also outdated. The Segway has already made cars obsolete. People just haven’t caught up with the times, man. And English? Why are we still talking in this archaic, inefficient language? Esperanto has made English obsolete. People are just oblivious to the inevitability of progress.


  8. drugmonkey Says:

    HyperCard stacks man. What would we do without those?


  9. MM Says:

    Rate of publication was explicitly commented on in the reviews of my fellowship apps.


  10. L Kiswa Says:

    “This advice already sounds outdated to me. I’m in a more computational subfield. I think many of us track preprint dates.”

    Awesome. Unfortunately, my dept chair (in a dept where half the faculty are computational; chair is also a computing guy) , dean, and T&P committee only care about pub date. From the few discussions I have had with folks at other schools, they are not very different in this regard.


  11. Emaderton3 Says:

    Gaps matter a great deal to reviewers, especially if you didn’t publish in a given year. I am happy to share the text from at least half a dozen summary statements I have from various agencies where reviewers have made comments. “PI has K award but has not been very productive . . .”


  12. qaz Says:

    In my experience, gaps are only a problem if not solved. If your track record has a burst of papers after a gap, that’s fine (because you’ve “solved the gap”). If your last paper was five years ago, that’s more of a problem. Since it is OK to list papers as “in press” (“submitted” and “in preparation” are different and do not count), having a mess of papers in press after a publication year should be fine.

    What I’ve seen (on study sections, in hiring committees, and in promotion committees) is that people tend to amortize the total number of papers by year up to the last published year and then to look at the in-press papers to ensure that you don’t have a gap since then.


  13. AcademicLurker Says:

    When assessing gaps, I think fairness requires considering funding gaps as well. I wouldn’t ding someone who had a thin publication record while their lab was on life support, especially not if they have a solid proposal. On the other hand, if someone had an R01 and failed to do anything with it…


  14. drugmonkey Says:

    I think fairness requires considering funding gaps as well

    This post was mostly about that extra bit of motivation to push a manuscript through to publication right now, i.e., I was assuming you have data enough to publish.

    But you raise a good point for discussion.

    Career review ain’t fair. It isn’t. Sure, there will be allowances made for your circumstances. The better the reviewers know you and the more favorably disposed towards your grant, promotion, etc then the more likely the allowances. But make no mistake. Nobody cares. Nobody cares because many, many people have bad things happen to them- personal circumstances, institutional circumstances, experimental circumstances. The default stance, fair or not, is that all else is equal so we will focus on what this person actually managed to accomplish.

    It is harsh but your career is going to be much better off if you act as though nobody gives a shit about your little problems* and do what you can to counter your deficits. Depending on the kindness of strangers to make allowances for your problems** is a route to disaster.

    *dude, I can tell you some stories

    **and yeah, I know, I know. You really did have some bad shit go down. I know. I sympathize*. I do. Now get back to work.


  15. drugmonkey Says:

    if someone had an R01 and failed to do anything with it

    I can remember a couple of reviews of competing continuations where the PI didn’t appear to do much with the award, it seemed to be double dipping on a single research program with multiple grants and, given my career stage at the time, I was really pissed off when they got fundable scores to continue. At least one of those cases became clear in retrospect that this sort of program-not-project based largesse for a midcareer asskicking investigator permitted a fascinating new line of attack. Work that would never have passed muster with reviewers if proposed for its own self. And it contributed to a sort of mega-across-the-lab’s-work set of studies that would likely not have happened without this research program being of the size that it was. I’m pretty sure I recall that the main theme of the specific project in question still hasn’t worked out to be anything useful.

    It’s a case study of this tension between funding projects and funding people/research programs. I think about it now and again.

    WRT your point, an interval of relatively low paper productivity for an entire R01 seems outrageous to those struggling to get their first one. unimaginable. But I’m not sure this takes a sufficiently broad view of the way science advances efficiently.


  16. AcademicLurker Says:

    Depending on the kindness of strangers to make allowances for your problems

    I guess I’m thinking of it less as kindness than as what I think my review should be addressing: “Will the NIH get a good return from funding this project?” If the PI was productive when they were funded, then that’s an indication that they’ll likely be productive once they’re funded again.


  17. drugmonkey Says:

    Yep. Sure. But there’s also “If they have a hard time getting one grant, what are the odds they will sustain a long term vigorous program?”. Prediction of the future from the past is a perilous game and everybody does it. Their predictions are biased HUGELY by their own trajectory and experiences. How can they not be?


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