Computational Interdisciplinarity: a Study in the History of Science (original) (raw)

2019

Abstract

This dissertation focuses on creating a pluralistic approach to understanding and measuring interdisciplinarity at various scales to further the study of the evolution of knowledge and innovation. Interdisciplinarity is considered an important research component and is closely linked to higher rates of innovation. To create more innovative research, one must understand how interdisciplinarity operates. This dissertation begins by examining interdisciplinarity with a small scope, the research university. Here, the study uses metadata and co-authorship networks to examine how a change in university policies can increase interdisciplinarity. The New American University Initiative (NAUI) at Arizona State University (ASU) set forth the goal of making ASU a world hub for interdisciplinary research. Here, interdisciplinarity is produced from a deliberate, engineered, reorganization of the individuals within the university and their knowledge. Using a battery of social network analysis measurements, an algorithm was created to measure the changes in co-authorship networks from increased university support. The second case study expands the scope of interdisciplinarity from individual universities to a scientific discourse surrounding the Anthropocene. The idea began as the need for a new geological epoch. It underwent unsupervised interdisciplinary expansion due to climate change integrating itself into the core of the discourse becoming an anchor point for new disciplines to connect and join the discourse. The scope of interdisciplinarity increases again with the final case study about the field of evolutionary medicine. Evolutionary medicine is a case of engineered interdisciplinary integration between evolutionary biology and medicine. The primary goal of evolutionary medicine is to better understand ”why we get sick” using an evolutionary biology framework. This study explores large-scale interdisciplinarity through networks and metadata analyses indicating that evolutionary medicine successfully integrates the concepts of evolutionary biology into medicine.

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