Flying far from the hive

Flying far from the hive

Flying far from the hive

How cultural differences between fields expand mindsets and methodologies

September 30, 2022 | Bernardo G.

Institute for Data, Systems, and Society

I’ve always enjoyed collaborating with people. You have fun, you make friends, and in the case of academic collaboration, it opens the door to addressing questions from diverse perspectives. When I first came to grad school, I wandered halls and labs looking for something interesting to do, and a great opportunity came after talking with my brother, then a Biology PhD student at the University of Sydney, to collaborate in estimating the average distances that bees fly. We divided the work: me, along with a professor who joined a few weeks after would tackle the estimation part, and the biologists would tackle the bees part. The collaboration was amazing! We had fun, we learned a lot about bee behavior and estimation techniques and wrote a paper (with a couple more in the works!). Since then, I have collaborated with health experts in USC, and economists at MIT and have found all my collaboration experiences to be nurturing. Specifically, I am right now working on an education project with a colleague from MIT Economics because we realized we had very similar interests. Teaming up allowed us to lead a huge project in Mexico to bring education to kids. While I have learned a ton from collaborating across different disciplines, I was shocked by the different “cultures” of the various academic tribes. Here I’ll share a few of the differences, and how we learned to work around them. 

First, an important difference between disciplines is related to authorship. Engineering authorship is organized as a function of each individual’s role in the project. Usually, the student who leads the effort will be the first author. In some cases, an asterisk is shared between a couple of the co-authors indicating that all performed equivalent work (in some papers it specifies that the order of the co-first authors was decided by a coinflip!) The name of the PI supervising the work and providing feedback is typically in the last position. The middle authors are usually people who collaborated on the project by providing ideas, work, old codes, or data. In economics, on the other hand, the order of authors is alphabetical. While this might seem just a format difference, it has great implications for collaborating. In engineering you can invite collaborators who will do less; but when you reach the final stage you’ll need agreement on the sorting of authors, and if things were not clear from the beginning of the collaboration, it may lead to some uncomfortable conversations. In economics, all authors will share equal credit and responsibility for getting the paper published. Neither format seems better or worse, but collaborations among the two groups can lead to misunderstandings if these differences are not addressed from the beginning.

The authorship has field-specific repercussions when students search for jobs after grad school: boards in engineering look for publications where you were a first author, while boards in economics look for publications where you were one author of a few. While the standard in engineering is that the PI of the home lab of the student will appear as an author given their role as supervisor, the standard in economics is that the professor will be on the paper only if they were the ones leading the project and creating the ideas. For collaborations between engineering and economics students, this creates some challenges. Do we keep the engineering PI out of the paper? Or do we include the economics professors but discredit the economics student by sending a signal that they did not lead the work?

What was our solution? Diversify the venues and journals where we publish our research. Collaborating is great, and it is even better when we keep in mind the end goals of everyone in the collaboration, and ensure that everyone’s hard work will be rewarded. In my case, we wrote at least two papers, one for an engineering audience where we can follow the engineering conventions; and one for an economics audience where we can follow the economics conventions. This allowed us flexibility in the structure of the collaboration and ensured that both sides were advancing their respective careers by seizing the great results successful collaborations can yield. When I collaborated with biologists, we came to a similar ideal solution. The estimation people wanted more estimation, the bee people wanted more bee biology. The solution was simple: we wrote a paper focused on the bees, their flight distributions and their implications for evolution and conservation, and another one focused on the estimation method, and how it can be applied to diverse fields. 

In my experience, collaboration is great. However, if I can give you a recommendation, it is very important to listen to your collaborators and not make assumptions that their field is exactly like yours. Sometimes we are so used to our discipline’s standards that we cannot imagine a different way to handle it. But if we listen and are willing to cross the bridge of collaboration, we will realize that each academic tribe has its own ways, but that is what makes collaboration so special. Once this bridge is crossed, interdisciplinary collaborations become incredibly fruitful as combining different perspectives often makes it possible to look at things in innovative ways. Moreover, people in different disciplines often have distinct talents; combining these virtues can make research projects more well-rounded as each person specializes in what they do best. Most importantly, when a problem is interesting to many different disciplines, it is likely to be a critical problem that requires many bright minds to arrive at a solution.

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