In a recent article, Deanna Pennington and her colleagues discuss how a diverse group of scientists from multiple fields figured out what was killing healthy young people in New Mexico in 1993. It was determined that a particular virus was causing the deaths, and that that virus lived in the common native deer mouse. To understand what was happening with deer mice, biologists, mammalogists, climatologists, and evolutionary biologists became involved with the medical community. The investigation led to several medical and epidemiological discoveries and also a link of the disease to the El Nino weather pattern and its related precipitation and how that affected deer mouse populations.
Once the virus was identified (by using then-sophisticated lab technology in the field for the first time), mammalogists used analysis of frozen specimens of deer mice in a museum to show that the virus was not new to deer mice, but only apparently new to people. But it turned out that it wasn’t even new to people — that Navaho healers had seen outbreaks of it before, and the timing of those outbreaks led to clues about how the virus was related to environmental conditions. Eventually that helped lead to the El Nino link.
What made this collaboration work?
The authors say the key human factors suggested are:
- Team members with a shared commitment to find a solution to the problem (which was helped in this instance by the life-and-death nature of the situation, and the crisis atmosphere)
- Deep knowledge in different fields of expertise
- A shared ethical and value system for collaborative engagement with the research team
- A position within highly connected knowledge networks
- Institutional access to the required funding, material, experimental and technological resources
In addition, the team had the material resources it needed — in terms of both data (like the frozen deer mice) and the tools (like the new analytical technique). While “institutional access” is listed as a human factor, you cannot have any kind of access to something that doesn’t exist — the “material resources” must exist.
The authors describe the challenges of working across disciplinary lines. It’s hard to understand what someone else means when they say something that practically “goes without saying” in their own discipline but is completely new to you. To help overcome the communication challenges, the team decided to use lists and other tools that make it easier to understand new (to some) concepts.
The article includes an interesting picture describing the process that the scientists went through as they moved to mutualism (supporting each other as a team), synthesis and integration of new ideas. The members of a group that developed out of the New Mexico virus team calls this the “Yatesian zone” in memory of one of their team members.
The arrows represent the paths of researchers who have deep knowledge of their own discipline and engage in transformative learning in another discipline. Initially, the concepts being learned are of low to intermediate depth in the new discipline and are unconnected with the researcher’s own disciplinary knowledge. Through critical reflection and reflective discourse with collaborators, they connect the new concepts to their own understanding; revise their mental models; and expand the conceptual, data, or technical foundations of their own discipline. This occurs concurrently among the collaborators. Once this has been achieved, they are able to collectively synthesize their new understanding into integrated conceptual frameworks that draw on deep knowledge from all disciplines, providing innovative research opportunities for all of the collaborators.
Anyone thinking about collaboration can benefit from a detailed study of how it really works when it works. It’s not all moving forward — there’s a lot of moving sideways. It requires opening one’s own mind, and relaxing one’s one mental models. It requires dealing with other people and what they know, and respecting that.
What other lessons do people have about what makes interdisciplinary collaboration work well?
Thanks, by the way to the publishers or editors of Bioscience, the journal in which this article was published, for making it available free on the Internet!! All quotes and near-quotes are from that article: Transdisciplinary Research, Transformative Learning, and Transformative Science by Deana D. Pennington, Gary L. Simpson, Marjorie S. McConnell, Jeanne M. Fair and Robert J. Baker BioScience (2013) 63 (7): 564-573.