Understanding and modeling social paths to integration in interdisciplinary teams
Résumé
Evaluating interdisciplinarity poses many challenges (Laursen, Motzer & Anderson, 2022), particularly building consensus on appropriate measures. Quantitative measures such as co-productions, collaborations, and studies of citation patterns get the most attention, leaving gaps in qualitatively understanding the role of social dynamics in knowledge integration, a recognized element of interdisciplinarity (Wagner, et al, 2011). Not understanding such social processes occurs at different granularities: institutional, community, team, and groups. These social processes all involve interactions with the interdisciplinary individual, but with varying aspects of context being foregrounded. Measures not only evaluate interdisciplinarity per se, but also conditions that may favor or hinder it.
Some gaps concerning social dynamics in this area are wider than others. Regarding institutions, requests for funding may require multiple disciplines, yet institutional criteria for promotion tend to remain discipline centred (Klein & Falk-Krzesinski, 2017), leading to social dynamics at cross-purposes. Similarly, implicit community rules may prod researchers to highlight work from their own community at the expense of more pertinent research published elsewhere (Porter, Roessner & Heberger, 2008), thus promoting having conversations with the “right people” over better citing practices. There is a vast body of work on groups involving the social processes by which people behave and how their characteristics may influence achieving group goals but fewer papers focus on the social dynamics specifically regarding knowledge integration from team members’ viewpoints vs. group members’. For example, Brodbeck, et al (2020) capture how complex decision-making profits from differentiation and integration of diverse perspectives and knowledge, but their experimental study does not give detail on how group social processes are related to knowledge integration. Molinari & Lund (2012) show how a power game shapes public recognition of knowledge integration between two students in a classroom but again, data did not involve scientific teams.
We propose emergent thematic coding analyses (Stemler, 2000), carried out on three datasets involving practicing interdisciplinary teams: 1) application documents for funding, 2) team-produced visualizations of interdisciplinarity and 3) two rounds of transcribed interview data with co-leaders. Each team co-leader is trained in different disciplines/subfields, mainly from human and social sciences, but not exclusively. Data is from 8 interdisciplinary projects, each financed at 230K€, and within a 5-year 4,3M€ project at crossroads involving overall more than 10 disciplines/subfields. We aim to develop a broadly based, team-level descriptive model on the role of social dynamics in knowledge integration, beginning with project planning, and moving through phases of research operationalization. We detail how ways of interacting between team members lead to specific types of integration, targeting ways of communicating with stakeholders in and out of academia, developing research questions, bringing to bear theories and concepts on project work, making decisions about gathering data, using analytical methods and tools, and disseminating results, all of which need socially based knowledge integration.
This area’s literature lacks precise definitions of social dynamics and social processes, and how, for example, social pressures, or emotional positioning of arguments (Polo, et al, 2016) play out in team-level interdisciplinary interactions in different phases. Our findings will allow us to build a descriptive model that fleshes out what is behind the label “social” through relevant and justified examples. The potential impact of such an exemplified model lies first in better understanding social paths to integration and secondly, in its use for interdisciplinary training.