| Popis: |
For several decades interdisciplinary research has been pushed by funding agencies, science administrators and generations of well-intentioned scientists. Interdisciplinary research is needed, so the argument goes, because the problems we face in medicine, environmental sciences, sociology or anthropology - the list can go on - are too complex to be mapped onto one traditional discipline. While the motivation for interdisciplinary research is clear, its actual success is less obvious. For one, we don’t quite know how to measure interdisciplinarity. While there have been many attempts at measuring interdisciplinarity, they typically refer to simple collaborations between field $A$ and field $B$ without taking into account the knowledge exchange at the heart of interdisciplinarity. Multiple studies find the need to distinguish interdisciplinary from multidisciplinary and transdisciplinary; where interdisciplinary combines disciplines in an integrative approach, multidisciplinary simply uses two separate approaches from different disciplines, and transdisciplinary occurs when disciplines are integrated but the product transcends disciplines and becomes more than the sum of its parts. Here, we exposed the heterogeneity of interdisciplinarity through computation. |
