2018
DOI: 10.1111/risa.13134
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Agent‐Based Models as an Integrating Boundary Object for Interdisciplinary Research

Abstract: Many of the most complicated and pressing problems in hazards research require the integration of numerous disciplines. The lack of a common knowledge base, however, often prohibits clear communication and interaction among interdisciplinary researchers, sometimes leading to unsuccessful outcomes. Drawing on experience with several projects and collective expertise that spans multiple disciplines, the authors argue that a promising way to enhance participation and enable communication is to have a common model… Show more

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Cited by 31 publications
(28 citation statements)
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“…The limited number of disaster research-focused methodological textbooks in the social and behavioral sciences (Norris et al, 2006; Phillips, 2014; Stallings, 2002) and public health (Institute of Medicine, 2015) are outstanding resources, but they do not consider the full range of approaches currently used by social scientists. This is, in part, because the social science methodological landscape has been rapidly transformed by the advent of big data, the introduction of new computational methodologies, and the increased participation of social scientists in interdisciplinary teams that are developing and using new methods and approaches (see, e.g., DeRouen & Smith, 2020; Gharaibeh et al, 2019; Nateghi et al, 2019; Reilly et al, 2018).…”
Section: Background On Sseermentioning
confidence: 99%
“…The limited number of disaster research-focused methodological textbooks in the social and behavioral sciences (Norris et al, 2006; Phillips, 2014; Stallings, 2002) and public health (Institute of Medicine, 2015) are outstanding resources, but they do not consider the full range of approaches currently used by social scientists. This is, in part, because the social science methodological landscape has been rapidly transformed by the advent of big data, the introduction of new computational methodologies, and the increased participation of social scientists in interdisciplinary teams that are developing and using new methods and approaches (see, e.g., DeRouen & Smith, 2020; Gharaibeh et al, 2019; Nateghi et al, 2019; Reilly et al, 2018).…”
Section: Background On Sseermentioning
confidence: 99%
“…In that sense, models can be a boundary object (i.e. platform that spans disciplinary boundaries to enable contributions and interpretations from diverse perspectives) in socioecological systems analysis [56]. One approach to innovate beyond the existing models is exemplified by the rapidly growing field of participatory modelling, which aims at engaging the knowledge of stakeholders to create formalized and shared representations of reality and using models as boundary objects to collectively reason about environmental problems and foster two-way learning [57,58].…”
Section: Learning From Modellingmentioning
confidence: 99%
“…Although the Reflective Listening Visualization as applied to the interview process was predominately qualitative, the designs that the team presented to the community in their final rendition utilized quantitative environmental science data regarding storm surge, water quality, water quantity, wind speeds and other measures and population projections, land ownership and land use from the social sciences. Finally, the Reflective Listening Visualization process incorporated and allowed for temporal dynamics as was one of the specified requirements of a boundary object by Reilly, Dillon-Merrill, & Guikema (2018).…”
Section: Reflective Listening Visualization and Communication Betweenmentioning
confidence: 99%
“…2002). The disaster literature is rife with examples of challenges with crossing disciplinary boundaries (Grigg, 1999) and, to a lesser extent, solutions for overcoming some of those challenges such as by integrating boundary objects as a common model that provides a means for interdisciplinary researchers to work toward a shared goal (Reilly, Dillon-Merrill, & Guikema, 2018).…”
Section: Introductionmentioning
confidence: 99%