How and why: complementary analyses of social network structures and cultural values: improving flood response networks in Queensland, Australia View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-01

AUTHORS

Elizabeth L. Malone, Susan Kinnear

ABSTRACT

Social network analysis (SNA) is well recognized as a tool for informing climate change adaptation; however, this methodology is limited by a focus on quantitative structural analyses (how many nodes and ties exist, and between whom), rather than accessing richer information about their meaning (value content of ties). One way to improve the usefulness of SNA is to purposefully complement the structural analysis with cultural elements that can be drawn from field datasets. In this network-governance case study from Queensland, Australia, research on organizations involved in water management and flood responses events showed that cultural values were important in influencing network connections and preferred approaches to flood pre-planning and response. For example, there were differences in organizational preferences for the numbers and types of links that are rooted in different values. From this, Mary Douglas’ Cultural Theory categories of individualists, hierarchists, and egalitarians were extended to analyze the types of ties between network nodes, the preferred approaches of different types of organization, and the problematic links and missing links among network nodes. This work illustrates that analyses of both structural SNA and cultural values can be used to improve regional-level adaptation activities such as disaster management. Here, increased knowledge about social networks, network ties, and cultural values can facilitate a process of social learning that will help societies adapt to climate change impacts. More... »

PAGES

203-220

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11135-013-9982-6

DOI

http://dx.doi.org/10.1007/s11135-013-9982-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049485411


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