Workshop: Many Voices, Nine Institutions- A Workshop with DC CHEERS
Facilitated by:
Randall Amster, Georgetown University
Tolessa Dekissa, University of the District of Columbia
Kari Fulton, Howard University
Jeremy Pittman, Environmental Defense Action Fund
Tara Scully, The George Washington University
Michael Svoboda, The George Washington University
Brooks Zitzman, The Catholic University of America
The concentration and variety of colleges and universities in this diverse city of 700,000 people—and their close proximity to the nation’s core institutions—make Washington DC a unique testing ground for cooperative thinking and action on environmental issues. DC CHEERS consists of faculty, staff, and students involved in sustainability operations and academic programs from nine universities in the metropolitan DC region. In this workshop, we invite participants from other places and institutions to join us in reviewing the DC CHEERS model for cooperative thinking and coordinated action through teaching, community engagement, and public advocacy. The workshop will involve participants in evaluating problems and opportunities we have identified and in brainstorming possible courses of action.
The three-hour workshop will be divided into three one-hour segments. The first will focus on the teaching of sustainability: What is taught? To whom? The second will address questions of environmental justice by examining how universities collaborate with their neighboring communities. And the third will envision our climate-changed futures in concrete, local terms. How do we acknowledge these formidable challenges without diminishing our capacity to respond? In each segment, the organizers will present material from their work with DC CHEERS; then they will invite attendees to contribute through brainstorming, freewrites, pair work, small group work/writing, roundtables, or directed discussion. In the final minutes of each segment, participants will be invited to offer their own summations. In this way, we hope others may be able to adapt elements of our model to their own circumstances.