Publications for the Job Market

The academic “job market” is one of those phrases I’ve heard numerous times but never really thought about until now. And now that I’m on it, I realize just how it really is like a market. There are a panel of buyers (universities, institutes, and hospitals) looking to bolster their faculty ranks, while applicants like myself are sellers, pitching their future potential and services. While there are certain traits all departments would want (eg. indicators of future publications / grants), different departments will be looking to shore up different parts of their research portfolios, and enact certain short- and long-term visions that you may contribute to if hired.

So this is a pretty complex system, where applicants like myself have a paucity of information (this is oftentimes our first experience with the academic job market, and it’s really hard to assess any precise estimates for probabilities of success). With such little information, it almost seems like you need to treat it as a bit of leap of faith, where you decide you need to give it your best shot and see where the offers (or lack of offers) fall into place, knowing it may end very well, very poorly, or anywhere in between.

While there are no hard rules that absolutely determine success or not, there are likely correlating factors, such as perceived future productivity in publications and grant writing. Much of this perceived future productivity is likely estimated by extrapolating from past productivity (ie. publications). Thus, I tried to see what the potential ranges of “strengths of publication histories” were for people who had just applied for faculty jobs (and succeeded, as they were now employed at a research university). I came up with a list of young PIs (many from websites of departments I’ve applied to), exported their PubMed histories as XML, parsed the XML, and scored each investigator by their cumulative “impact score”. This impact score was a completely arbitrary metric I cooked up, where an investigator is given full impact points of the journal they were published in if they were first author, dividing by two if it was a review article rather than a research article, and additionally dividing by two or four if they were second or third author, respectively (anything past that was automatically weighted a tenth). Yes, this is a HORRIBLE metric that 1) Certainly does not actually capture a person’s scientific contributions, and 2) May not be anywhere near even accurately capturing “perceived” scientific contributions from faculty in search committees, especially since everyone likely interprets them differently. Still, to these critical flaws, I argue that even having something imperfect / inaccurate is at least some form of information, which in this case, is better than no information at all (which is what I’m currently working with as an applicant estimating the perceptions of selection committees).

I did this for a panel of ~100 young PI’s, and then included myself in the analysis, to see where I fall in the distribution. The results:

So I think this is somewhat personally reassuring; My history of publications, by this totally-imperfect-but-hopefully-remotely-useful metric, ranked partway through the distribution of success cases. I think the only real takeaway is that my publication history is at least in a range that has been able to get other people faculty jobs, so I’m not completely fooling myself in thinking I could be competitive in the job market.

The data actually breaks down more individually like this (I’ve largely redacted the names, as not to offend anyone or make them feel trivialized or powerless by being mentioned here):

Unfortunately, another critical flaw to this analysis is that there is a clear bias in the data that’s available, where it’s relatively easy to identify success cases (albeit even this is biased by the types of institutions I look at to find assistant professors), but damn near impossible to find failed cases (people who tried to go on the job market, and couldn’t end up with a job). Thus, it’s impossible to really benchmark this metric, or come up with an objectively more accurate one. But still, I think there is some value in knowing that your resume looks about as strong as other people who have succeeded, and that while that may not be easy to change anytime soon, at least there are other factors you can still control (such as thoughtful preparation, both for the application or otherwise, that may help compensate for other deficiencies).