Assessing improvements in socio-ecological system governance using mixed methods and the quality governance framework and its diagnostic capacity tool

Abstract

We face extreme and unprecedented socio-ecological systems (SES) governance challenges given advances in technology, global biophysical change, human behavior, and our abilities to seek resilience through policy decisions. The associated demands to rapidly adapt and shift our trajectories for improved SES outcomes provide a great impetus for humans to improve upon complex SES governance quality. Building on theories derived from polycentric, participatory, network-based practices, structured deliberative decision processes, and capacities that align with resilient systems thinking, a Quality Governance Framework (QGF) and Diagnostic Capacity Tool (DCT) were developed to diagnose SES governance quality that could improve outcomes for a cleanup and redevelopment program in Michigan. The QGF and its DCT were found to be reliable and valid. Using a subset of the DCT measurements and other respondent data, this research uses a mixed methods approach to further test and validate the QGF and DCT. The cleanup program was in its third year of transitioning from a more hierarchical form of governance to one that is more participatory. The results indicate further convergence in ratings between previously disparate practitioner populations and increases in the perceptions of improved governance quality and resilient SES outcomes. Respondents’ open-ended feedback and program metrics correlate with the DCT findings and provide further validity for the QGF and competencies associated with quality governance measured with the DCT. This research contributes to the growing body of empirical evidence that can assess governance quality and illuminates how governance quality can be diagnosed to treat and improve SES outcomes.