Measuring the Transition to Sustainability: From Simple Diagnosis to Data-driven Interventions

Thomas B. Cook
Md Rumi Shammin, Oberlin College
Cynthia M. Frantz, Oberlin College
John E. Petersen, Oberlin College


The development of metrics based on quality data that track the state of physical, economic, and social systems— particularly in response to interventions designed to increase sustainability—is a necessary (though not sufficient) condition for intelligent decision making. Thus far, efforts to measure progress towards sustainability goals have focused at geographical and temporal scales that are not always suitable for quantifying community-level processes or assessing the efficacy of community-level interventions. Furthermore, they typically emphasize economic and biophysical attributes and fail to adequately capture critical social dimensions that may drive the other processes. We report here on initial efforts to develop and validate community-level sustainability metrics that emphasize the crucial role of social factors in driving the transition to sustainability.