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arXiv · 1806.11433

Team assembly mechanisms and the knowledge produced in the Mexico's National Institute of Geriatrics: a network analysis and agent-based modelling approach

Carmen García-Peña·Luis Miguel Gutiérrez-Robledo·Augusto Cabrera-Becerril·David Fajardo-Ortiz
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Abstract

Mexico's National Institute of Geriatrics (INGER) is the national research center of reference for matters related to human aging. INGER scientists perform basic, clinical and demographic research which may imply different scientific cultures working together in the same specialized institution. In this paper, by a combination of text mining, co-authorship network analysis and agent-based modeling we analyzed and modeled the team assembly practices and the structure of the knowledge produced by scientists from INGER. Our results showed a weak connection between basic and clinical research, and the emergence of a highly connected academic leadership. Importantly, basic and clinical-demographic researchers exhibited different team assembly strategies: Basic researchers tended to form larger teams mainly with external collaborators while clinical and demographic researchers formed smaller teams that very often incorporated internal (INGER) collaborators. We showed how these two different ways to form research teams impacted the organization of knowledge produced at INGER. Following these observations, we modeled, via agent-based modeling, the coexistence of different scientific cultures (basic and clinical research) exhibiting different team assembly strategies in the same institution. Our agent model successfully reproduced the current situation of INGER. Moreover, by modifying the values of homophily we obtain alternative scenarios in which multidisciplinary and interdisciplinary research could be done.

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Carmen García-Peña, Luis Miguel Gutiérrez-Robledo, Augusto Cabrera-Becerril, David Fajardo-Ortiz. 2018-06-21. Team assembly mechanisms and the knowledge produced in the Mexico's National Institute of Geriatrics: a network analysis and agent-based modelling approach. https://doi.org/10.1155/2019/9127657

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