Sensemaking: a complexity perspective

• Main Authors: Timothy Lynam, Chris Fletcher
• Format: Article
• Language: English
• Published: Resilience Alliance 2015-03-01
• Series: Ecology and Society
• Subjects: adaptation; climate change; complexity; micronarratives; mixed methods approach; narratives; sensemaking; stages of change (SOC); transtheoretical model
• Online Access: http://www.ecologyandsociety.org/vol20/iss1/art65/

Our intent was to provide a methodological overview of the primary data collection process in support of the other articles in this special issue. We documented and illustrated the use of a data collection and analysis suite, SenseMaker, that was designed to collect and work with narrative fragments. The approach presented adds a new and inherently mixed tool to the mixed methods toolbox. Despite its novelty and potential utility, little has been written in the academic literature on the application of SenseMaker to complex problems. To the best of our knowledge, the approach has not been used in relation to climate change or climate change adaptation and has not been presented in the mixed methods literature. We sought to contribute to filling this gap through describing the approach used to generate the data that underpin the articles in this special feature. Our purpose was to illustrate some of the potential and most notable challenges of using the SenseMaker data collection and analysis process in a complex domain through examining adaptation to climate change. Our overview was not exhaustive but rather sought to highlight capabilities and challenges through examining experiences of adaptation from a stages of change perspective. SenseMaker provides a remarkably powerful tool for the capture of micronarratives of complex phenomena such as climate change. The capacity to have respondents interpret, i.e., make sense of, their own narratives is an important innovation that provides one plausible solution to the problem of analysts coding narratives. Analytically, however, SenseMaker is relatively weak for those seeking strong statistical support for analyses and provides no capability for analyzing the narratives themselves.