As new PhD students start to look forward to their first year, short 🧵 on challenges in collaboration in grad school (and its potentially gendered dimensions).
Many people advise grad students to rely on their classmates: first in coursework, later on projects / as coauthors.
I endorse that advice! But it can also be hard to follow. I attended two grad programs (MPhil and PhD) and had similar experiences in both. There were large, energetic, overlapping-networks problem set groups that formed quickly.
They were mostly dominated by men (unsurprisingly; econ grad programs are mostly dominated by men) and, to describe it neutrally, had a fast-paced style. Always an introvert who was becoming more so, I was uncomfortable and anxious about trying to participate.
My math and programming background was relatively weak, and fair to say I was wrestling with my overall level of interest in economics. At Oxford, I wouldn’t even work in the same library as my classmates; I did occasionally compare psets with 1 or 2 people.
In my PhD, I had a small and awesome pset group (hi @ElizaForsythe!) That helped a lot. Still, I was certainly out of the loop; my network was thin, and continued to be thin as I moved into dissertation writing and the challenges of this pattern became more obvious.
I didn’t share that much, didn’t get that much feedback; socializing with classmates often made me anxious. At the time I graduated, I had only one project joint with a cohort-mate. Later added 2 more with other classmates.
But, my network is still mostly populated with connections from much later. Those connections are awesome (as are my coauthors from MIT)! But, I’m aware that I missed out on a lot, particularly early on.
My suggestions? Not sure! It’s great to jump into as many networks as you can in a PhD program, and work a lot with classmates. I am the first to say that can be challenging, and I think this is true particularly for women and, I imagine, for URM or first-gen students.
I gravitated toward very compact groups, mostly with other women, where I felt more comfortable; this has costs and benefits. Introverts, consider seeking out other quieter classmates at first to work with or even chat with (believe me, there are others out there).
This might be a place to build confidence and then branch out (unfortunately I largely didn’t do the latter).
Another option: just set very concrete, specific goals. At some point I had the goal of asking one question per weekly grad student lunch.
As ridiculous as it sounds, it was unbelievably hard, but I did largely stick to it. I wish I had set other similar goals around getting feedback from classmates, considering joint projects, proposing ideas. I still use the minimal-goal strategy sometimes today, when needed.
Hope this helps for those starting grad school and thinking about how to benefit from as well as enjoy it. 100% true that it's easier with friends, but if you find it hard to make those friends sometimes: you're not the only one!
Enjoyed the presentation by @elianalaferrara today at World Bank DIME of work joint with Baumgartner, Rosa-Dias, Breza and my awesome coauthor Victor Orozco: evidence around a peer education program targeting early sexual activity teen pregnancy in Brazil.
The authors have a fascinating evaluation comparing a peer educator program with three alternate selection mechanisms for educators (school-driven; selection via peer nomination of popularity; selection by centrality in a formally mapped network) to a control arm.
In general, the peer education program is very effective: ⬆️ knowledge and communication around sexuality, contraceptive use; ⬇️ teen pregnancy. The peer educators chosen by schools (the default method), however, were generally ineffective!
So much of what we hear around RCTs are exciting stories about how evidence is used to inform policy. Which is awesome! I love evidence-informed policy. However, I'm sure many of us have also had experiences that are different, and more challenging.
In the spirit of transparency, wanted to share some different (anonymized) stories about use of evidence. Short 🧵
#1: program has mixed effects (largely null for downstream outcomes). Funding for the implementer concludes, implementer and funder move on. What happens? Brief discussion, draft paper shared (0 replies), almost no policy learning (hopefully research community benefits).
Lately I’ve been thinking more and participating in various conversations about how USAID commissions, uses research. Huge topic! But wanted to do a short🧵on what I’ve learned. 1/n
First and foremost in the hearts of most economists is DIV. DIV is awesome, as many others have pointed out! See this recent blog by @DaveEvansPhD and colleagues 2/n cgdev.org/blog/case-evid…
But, DIV primarily funds evaluation of pilots and other interventions that are implemented outside of USAID and are not directly related to the work of missions – as summarized above (there are some exceptions). In that sense it is often separate from the main aid portfolio 3/n
After doing a lot of reformatting to meet a journal page limit (which, TBC, I support), I started to wonder - why don't journals impose limits on the referee reports that lead to these long papers? E.g., 1-2 pages; or alternatively, 3-5 (choose N) substantive suggested revisions
Seems like this could help with a lot of problems - long review times, tedious revisions, bloated papers that are hard to read, indigestible appendices, etc. Hard to enforce, but editors could suggest that material beyond the limit would be ignored.
Plus, I suspect many referees would be very happy for explicit guidance that allows for coordination, since (many of us) are concerned about the perception of submitting an un-thorough or low-quality report relative to others. . .
Happy to see the latest JEP table of contents and took a look at the @bfjo paper on teamwork right away (h/t @jenniferdoleac). Really fascinating and some striking graphics on the rise of teamwork in econ; short 🧵 #EconTwitter
On a subfield note, was very surprised to see development was significantly under the average for team size in the 1980s, though it has now converged up. Anecdotally it seems like much larger teams (5+, 10+) starting to surface in dev, still rare in the profession at large
Also a thoughtful discussion of questions about credit, attribution and equity. Lots of evidence already that some team members (particularly women) receive less credit than others, e.g. Sarsons et al. journals.uchicago.edu/doi/abs/10.108…
New week, new twitter project! In recent years more and more randomized trials have analyzed interventions targeted at non-cognitive skills (soft skills, life skills, socio-emotional skills) broadly defined in developing countries. 1/n
This is a major interest of mine – I’ve decided to start a running thread quickly summarizing and linking to papers of interest. Please add links to other papers, including your own – I’ll add them. 2/n
Two today. First, Acevedo, Cruces, @paul_gertler, and Martinez analyzed a soft skills and vocational skills training program in the DR. Targeted skills include grit (perseverance, ambition) and social competencies (leadership, conflict resolution, social skills, empathy) 3/n