So say I have been considering a return to academia for a graduate degree that will let me operate at the level in an organization that I'd prefer to work at. Are there antipatterns that work in the other direction that I should know about beforehand?
masters is honestly just like undergrad but a bit more intense, I think.
so for that case, no. my guess is that you might trample over some delicate tacit academic norms but it probably won't matter if you do because people are too afraid to speak up about anything.
a doctoral program is different and I'd be happy to talk about that at length but it's an entire post unto itself, and I might not be qualified to write it (I was not great at graduate school)
PhD. My understanding is that in addition to the net cost being lower (more funding available to cover tuition+expenses), a PhD program can be ended prematurely and a master's degree awarded based on achieved coursework to prevent dropout stats from going up.
Yeah--the extent to which this is true varies by program but it's pretty common to permit courtesy master's degrees for people who finish their coursework but not their dissertation (I am one such person).
My guess is that you still come out roughly ahead in terms of being able to speak more confidently as someone who's had a life outside of school, and probably more able to focus on the salient parts of work. This is very off the cuff for me and I'm not completely sure about it, though. And I'm having a hard time envisioning the downsides, having never been in that position, but I'm sure they exist. Potentially, just not being aware of the signaling games that others are playing.
I guess one thing to consider is that industry careers are often looked down on by faculty as a bad outcome, and so if you're open about the fact that you plan on going back to private sector work it's plausible you'll get the cold shoulder from faculty and may have a challenging relationship with your advisor. This is pretty dependent on faculty member, though.
So many thoughts on this as someone who did a diss using econometrics and now works in a non-academic role.
Every so often I get asked to do a brown bag or class on how to communicate with statistics to legislators and policy types. My primary message always is to use the simplest possible presentation--if clear descriptive statistics can do it, that’s great. If OLS is required, or even worse logistical regression, you CAN explain but you increasingly are going to have to rely on them basically trusting you. If your’re getting into the arcana of various robust regression estimators, well, friend, you’re doing that for yourself and hopefully for the correct reasons (e.g., you have a reason to believe they’re necessary like trimming outlier influence) and you shouldn’t expect your care will be even noticed by, well, anyone.
What’s far more troubling to me, though, is the reaction of academics to practitioners trying to enter into the academic debate. You will find over and over again that even though you have access to data that academics should dream of (in my cases, linked arrest and prison records by inmate and linked K-12/higher ed prep records by SSN) it doesn’t matter. You will have access to to new and untapped resources and you. Will. Not. Get. Published. Either your operational data isn’t a perfect control, or there will be dark mutterings about collider variables, or you’ve haven ‘t employed the latest hyper-specific regression technique from a journal two years ago you don’t have access to. And it won’t matter that even your summary statistics will have more real world impact than a career of academic esoterica.
What was your field of study? I’m a postdoc doing complexity theory (approximately pure math) and this characterization of academia doesn’t match my experience.
What was your field of study? I’m a postdoc doing complexity theory (approximately pure math) and this characterization of academia doesn’t match my experience.
I am someone who left academia, I was longsighted enough to figure oy quickly that the environment wasn't for me. However, I also had a great time in academia, I met some awesome people and I learned a lot. Anyway, my point is that while I agree on a general grounding with this post, I think it tends to generalise a bit too much. Two examples: industry people being more extroverted and having an attitude for doing things. The industry world is huge and varied and things aren't that simple - there's a lot of different situations, good and bad, everywhere. For me the main reason to leave academia was feeling that I didn't have full freedom, that my career was not really for me to shape but rather depended on relations and red tape. I definitely felt much better outside immediately, but that's not to say that there's always a good mindset overlap - culture is culture and companies can have widely different ones.
This is good advice for most people, not just those leaving academia
So say I have been considering a return to academia for a graduate degree that will let me operate at the level in an organization that I'd prefer to work at. Are there antipatterns that work in the other direction that I should know about beforehand?
hmm--for a PhD or for a master's?
masters is honestly just like undergrad but a bit more intense, I think.
so for that case, no. my guess is that you might trample over some delicate tacit academic norms but it probably won't matter if you do because people are too afraid to speak up about anything.
a doctoral program is different and I'd be happy to talk about that at length but it's an entire post unto itself, and I might not be qualified to write it (I was not great at graduate school)
PhD. My understanding is that in addition to the net cost being lower (more funding available to cover tuition+expenses), a PhD program can be ended prematurely and a master's degree awarded based on achieved coursework to prevent dropout stats from going up.
Yeah--the extent to which this is true varies by program but it's pretty common to permit courtesy master's degrees for people who finish their coursework but not their dissertation (I am one such person).
My guess is that you still come out roughly ahead in terms of being able to speak more confidently as someone who's had a life outside of school, and probably more able to focus on the salient parts of work. This is very off the cuff for me and I'm not completely sure about it, though. And I'm having a hard time envisioning the downsides, having never been in that position, but I'm sure they exist. Potentially, just not being aware of the signaling games that others are playing.
I guess one thing to consider is that industry careers are often looked down on by faculty as a bad outcome, and so if you're open about the fact that you plan on going back to private sector work it's plausible you'll get the cold shoulder from faculty and may have a challenging relationship with your advisor. This is pretty dependent on faculty member, though.
I would be very interested in such a post
So many thoughts on this as someone who did a diss using econometrics and now works in a non-academic role.
Every so often I get asked to do a brown bag or class on how to communicate with statistics to legislators and policy types. My primary message always is to use the simplest possible presentation--if clear descriptive statistics can do it, that’s great. If OLS is required, or even worse logistical regression, you CAN explain but you increasingly are going to have to rely on them basically trusting you. If your’re getting into the arcana of various robust regression estimators, well, friend, you’re doing that for yourself and hopefully for the correct reasons (e.g., you have a reason to believe they’re necessary like trimming outlier influence) and you shouldn’t expect your care will be even noticed by, well, anyone.
What’s far more troubling to me, though, is the reaction of academics to practitioners trying to enter into the academic debate. You will find over and over again that even though you have access to data that academics should dream of (in my cases, linked arrest and prison records by inmate and linked K-12/higher ed prep records by SSN) it doesn’t matter. You will have access to to new and untapped resources and you. Will. Not. Get. Published. Either your operational data isn’t a perfect control, or there will be dark mutterings about collider variables, or you’ve haven ‘t employed the latest hyper-specific regression technique from a journal two years ago you don’t have access to. And it won’t matter that even your summary statistics will have more real world impact than a career of academic esoterica.
based
What was your field of study? I’m a postdoc doing complexity theory (approximately pure math) and this characterization of academia doesn’t match my experience.
What was your field of study? I’m a postdoc doing complexity theory (approximately pure math) and this characterization of academia doesn’t match my experience.
I am someone who left academia, I was longsighted enough to figure oy quickly that the environment wasn't for me. However, I also had a great time in academia, I met some awesome people and I learned a lot. Anyway, my point is that while I agree on a general grounding with this post, I think it tends to generalise a bit too much. Two examples: industry people being more extroverted and having an attitude for doing things. The industry world is huge and varied and things aren't that simple - there's a lot of different situations, good and bad, everywhere. For me the main reason to leave academia was feeling that I didn't have full freedom, that my career was not really for me to shape but rather depended on relations and red tape. I definitely felt much better outside immediately, but that's not to say that there's always a good mindset overlap - culture is culture and companies can have widely different ones.