Negotiating a Future That Is Not Like the Past

Autor/inn/en	Elsenbroich, Corinna; Badham, Jennifer
Titel	Negotiating a Future That Is Not Like the Past
Quelle	In: International Journal of Social Research Methodology, 26 (2023) 2, S.207-213 (7 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1364-5579
DOI	10.1080/13645579.2022.2137935
Schlagwörter	Models; Futures (of Society); Research Methodology; Systems Approach; Change Agents; Decision Making; Policy Formation; Prediction; Data Analysis; Educational Planning; Well Being; COVID-19; Pandemics; Foreign Countries; Simulation; Social Change; Public Policy; Public Health; Vignettes; United Kingdom (England) + Suchen Sie Ihr Suchwort? Analogiemodell; Future; Society; Zukunft; Research method; Forschungsmethode; Systemischer Ansatz; Decision-making; Entscheidungsfindung; Politische Betätigung; Vorhersage; Auswertung; Bildungsplanung; Well-being; Wellness; Wohlbefinden; Ausland; Simulation program; Simulationsprogramm; Sozialer Wandel; Öffentliche Ordnung; Gesundheitswesen
Abstract	Agent-based models combine data and theory during both development and use of the model. As models have become increasingly data driven, it is easy to start thinking of agent-based modelling as an empirical method, akin to statistical modelling, and reduce the role of theory. We argue that both types of information are important where the past is not a reliable blueprint for the future, which occurs when modelling dynamic complex systems or to explore the implications of change. By balancing theory and data, agent-based modelling is a tool to describe plausible futures, that we call 'justified stories'. We conclude that this balance must be maintained if agent-based models are to serve as a useful decision support tool for policymakers. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01