Editor’s Note: I attended an ASA Chair’s meeting and spoke about ways we could support junior faculty in data science. After giving my talk Galin Jones, Professor and Director of Statistics at University of Minnesota, and I had an interesting conversation about how they had changed their promotion criteria in response to a faculty candidate being unique. I asked him to write about his experience and he kindly contributed the following post.
If the number of looming deadlines on my calendar for recommendation letters is any indication, we are squarely in application season for tenure-track faculty positions with interviewing season soon to follow.
When candidates for junior faculty positions come for an interview, the requirements for promotion are at the forefront of the discussion. This is perfectly rational. After all if the path to promotion is unclear or is going to require participation in activities that are different than what you are excited about, why take the job?
What most candidates are told is essentially the same thing I was told in 2001 and others were told in 1991 and so on. Be good at research, teaching, and service. Try to get an external research grant. (In biostat departments, there is more discussion about external funding.) But the subtext of the conversation is that research is the primary concern and to be good at research the focus should be on quality, with a nod to productivity. This is often code for publishing as many articles as possible in the big four journals–JASA, Biometrika, JRSSB, and the Annals of Statistics.
While this has been the traditional approach, it ignores the way the field has changed and doesn’t make any serious attempt at assessing true impact on the discipline or more broadly. Collaborative projects, refereed conference papers, software development, software vignettes, blog posts, videos, podcasts, development of novel teaching methods (MOOC anyone?), and so on are often viewed as being helpful to the P+T case only if they connect directly to a paper published in a traditional statistics journal.
The School of Statistics at Minnesota is no different than others in this regard, but we have at least partially realized there is an issue. A while back we interviewed a candidate for a junior faculty position. This person showed a lot of promise, had a novel research agenda, and obviously was going to impact the profession albeit in nontraditional ways. But that candidate could not be promoted under our P+T guidelines at the time so we could not in good conscience make an offer. I think it is to our credit that our faculty debated the issue and overwhelmingly agreed to modify our P+T guidelines so that things like software development, vignettes, and conference publications apply toward promotion and tenure. Our P+T guidelines are not necessarily where I’d like them to be, but this was a sort of progress at the time.
I fear that if (bio)stat departments continue to limit evaluation criteria to the traditional ones, then it will become increasingly difficult to recruit and retain faculty since there are so many alternative opportunities where the new approaches are encouraged. On the other hand, if we broaden what is recognized, we have a much better chance to attract and retain faculty that are taking advantage of the new opportunities available to (bio)statistics students.comments powered by Disqus