Another aspect of a recent Careers Discussion with my research group involved talking about the elements of a Professorial Trading Card from PhD comics. The "trading card" was very useful for illustrating important topics that most of us somehow learn at some point, typically on a need-to-know basis at different stages of an academic career.
I thought it would be good to discuss these issues head-on with the group, even though the card is focused on statistics mostly relevant to a research-focused career at a university. For those not interested in this career path, the "trading card" can at least help demystify some of the aspects of the professional lives of grad advisors. The card shows:
Prof. X (photo of bearded guy, but you can download a template and put in your own photo)
professorial rank
team: "His own." (the only part of the professorial trading card I didn't like, maybe because I am in a field that is highly collaborative)
T (= tenured)
Academic stats:
Research buck$ in: Grad students, do you have any idea how much grant $ your advisor has? Do you want to know? If you do and you don't want to ask, you can look it up on many major funding agency websites.
Papers written: Although of course quality is more important than quantity blah blah blah, we do count these. Many (most?) academics can tell you exactly how many papers they have published. If you want to know someone else's paper count, this is easy to find via Web of Science, Google Scholar etc., keeping in mind that the total is not typically exactly correct.
h-index: This glorious concept was news to some in my research group, but now they all know what it is. Important?!
PhD students graduated: Our group maintains a director of alumni/ae, so this information is accessible.
PhD students dropped out: This information is not accessible in any systematic way, but I suppose a grad student could ask around and at least get a sense for whether the "drop out" rate was high for a particular advisor or research group.
Awards: Who cares? Professors and administrators do!
Invited lectures: a measure of the level of interest of a professor's research and/or the level of interest of a professor in traveling around and giving talks when invited.
Then there are some miscellaneous statistics on the "trading card", mostly to maintain the analogy with a baseball trading card: doubles = two papers on same topic; triples = three papers using the same dataset; stolen postdocs (?).
Despite some odd aspects of the Professorial Trading Card, I found it a useful focus for discussing some key issues of academic jobs, at least at a big research university: the focus on grants, papers, citation index, PhD students graduated, and so on. These seem obvious to those of us who have been living in this world for a long time, but it can be interesting and useful (and perhaps alarming) to discuss them with students and postdocs.
Although the trading card lists many key aspects of the professorial job at a university, is there anything important missing from the trading card? How about:
Number of postdocs?
Number of grants (not just the $ amount)?
Number of graduate students and postdocs employed in PhD-relevant jobs?
Number of courses taught? (at different levels?)
What else?
14 years ago
17 comments:
Average time for students to graduate
Proposal success rate
Average reviews for teaching classes
Consulting fees charged
That'd be my additions
Number of chili peppers on RMP?
OK - from a humanties professor at a SLAC - what is an H-index?
What is the h-index?
I'd have had "grad students stolen" the bases stolen. Post docs are less valuable because (though potentially more efficient) cost more, and basically working at a job, not as an indentured servant who will "double count" in many areas: number of students graduated, grad rate, etc.
In grad school, we had a kerfuffle because Jr. Faculty had recruited 5/10 of the incoming grad students to the program. Sr. Faculty viewed this as "poaching" as it denied him those student resources.
-How many of your grad students are on antidepressants who never took them before working in your group
-Years to graduate is key for grad students, especially in the US, where it can draggggggggg onnnnnnnnn.
-Average evals for classes taught
-Count of citations of most cited paper
-# of years on the job
PhD Comics is so funny! Have you ever seen Jorge Cham live? He is so funny.
Somewhat interesting that there is not a word about undergraduates and their training....given the increasing focus on undergraduate training at legislative levels, it might also be useful for a prospective graduate student to know how undergraduates factor in the training they'll receive.
Good point. I keep track of the number of my undergrad research advisees: summer interns and students from my own university. Some of these are now professors.. making me feel old, but in a good way because it is so extremely cool to see them do well in their careers as scientists. #URA = number of undergrad research assistants could be a number on a professorial trading card. It will probably correlate with size of lab/research group, but it might show whether advising undergrads is a priority for a professor.
AGE. (Or years since PhD)
Ok, doesn't generate the full "trading card", but a nice quick way to see the H-index and other useful information is to put your advisor into http://readermeter.org/
Perhaps one day CVs and other information about advisors, students, job candidates, will be generated by such tools?
Total number of academic descendants, as a proxy for how well your students have done. Of course, this can't become large until one's career has advanced fairly far, and this doesn't count students who have gone on to interesting and useful non-academic jobs.
@Andrea
An H-index of N means that you've published N papers that have each been cited at least N times.
So person who publishes tons of papers that everyone ignores and a person who got lucky once with a single highly cited paper would both have a low H-index.
In my department, # of advisees (undergrad, grad) is not correlated with age/career stage of professor.
Height and weight
@ Stephanie: I've been joking lately about getting IRB approval to do a study on that. Including sleeping pills, anxiety meds. And tie it to advisor/program issues. Cause the results would be scary, at least where I am.
Carl - at least for the people I've looked up, ReaderMeter is VERY inaccurate. The stats seem to depend entirely on who is signed up to Mendeley. It split my publications between 2 people and still gave me a higher H-index than my old supervisor (his real H-index is 3 times mine).
Scopus or ResearcherID are both better.
@carl & @anonymous(4:27 a.m.) - readmeter is all about alternative metrics of publication impact, using the quantity of social bookmarking not citations. So, the information provided by the site is couched in the same language as traditional citation based metrics, but it's based on a completely different kind of data.
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