Toward a Pluralistic Conception of Resilience

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Matteo Convertino, James Valverde


The concept of resilience occupies an increasingly prominent position within contemporary efforts to confront many of modernitys most pressing challenges, including global environmental change, famine, infrastructure, poverty, and terrorism, to name but a few. Received views of resilience span a broad conceptual and theoretical terrain, with a diverse range of application domains and settings. In this paper, we identify several foundational tenets --- dealing primarily with intent/intentionality and uncertainty --- that are seen to underlie a number of recent accounts of resilience, and we explore the implications of these tenets for ongoing attempts to articulate the rudiments of an overarching resilience paradigm. Firstly, we explore the complemental nature of risk and resilience, looking, initially, at the role that linearity assumptions play in numerous resilience frameworks found in the literature. We then explore the limitations of these assumptions for efforts directed at modeling risk and resilience in complex domains. These discussions are then used to motivate a pluralistic conception of resilience, drawing inspiration and content from a broad range of sources and empirical domains, including information, network, and decision theories. Secondly, we sketch the rudiments of a framework for engineered resilience, the primary focus of which is the exploration of the fundamental challenges that system design and system performance pose for resilience managers. The conception of engineered resilience set forth here also considers how challenges concerning time and predictability should factor explicitly into the formal schemes that are used to represent and model resilience. Finally, we conclude with a summary of our findings, and we provide a brief sketch of possible future research directions.



Applied Mathematics, Computer Sciences, Dynamic Systems, Ecology and Evolutionary Biology, Environmental Health and Protection, Environmental Indicators and Impact Assessment, Environmental Monitoring, Environmental Sciences, Life Sciences, Medicine and Health Sciences, Natural Resources and Conservation, Numerical Analysis and Computation, Other Medicine and Health Sciences, Other Physical Sciences and Mathematics, Physical Sciences and Mathematics, Social and Behavioral Sciences, Sustainability, Systems Biology


decisions, foundations, intentionality, networks, resilience, systemic risk, uncertainty


Published: 2019-06-29 11:53


CC-By Attribution-ShareAlike 4.0 International