Learning from sticky variables in cross-case analyses of collaboration in social-ecological systems

Abstract

ABSTRACTThe importance of collaborative approaches to governing social-ecological systems (SES) towards more transformative outcomes is now widely acknowledged. Theoretical and meth- odological frameworks to enable such collaborations are being developed across a range of disciplines. Transdisciplinary approaches are emerging as a key enabler of potentially trans- formative collaborations in SES, particularly where these are characterized by ‘multiple multi- ples’ (e.g. multiple scales, knowledge systems, etc.). A typical approach to studying complex collaborative initiatives across a range of contexts is comparative case study research, often relying on researchers embedded in cases. In this approach, qualitative case studies are coded using predetermined variables (based on ecological, social, and social-ecological features of cases) to enable comparison and cross-case analysis. In our experience, the process of coding qualitative cases into a quantitative analysis framework can be hampered by what we term ‘sticky variables’, i.e. variables which are difficult to code for reasons related to aspects of the intrinsic complexity of social-ecological systems. Based on cases from a range of geographic locations across the Global North and South, we identify sticky variables, and elucidate the reasons for their ‘stickiness’. We propose several ways of working with and learning from sticky variables, and we reflect on theoretical, methodological and reflexive aspects of transdisciplinary research on collaborations. Moreover, we suggest that sticky variables might be ‘flags’ for interesting underlying factors that influence collaboration. We conclude by drawing out recommendations for researchers and practitioners confronted with the complexities and nuances of collaborations in social-ecological systems around the world.

Keywords

• Nadia Sitas
• Social-ecological systems
• collaboration
• user rights
• adaptability
• shared vision