CFP: Grounding Disaster STS

Grounding Disaster STS

Science and Technology Studies is fluent in the social and cultural aspects of risk, technological fixes, uneven vulnerability, complex infrastructure, and the sciences that define, measure, and evaluate harm. In the context of a new normal characterized by extreme weather, ubiquitous contamination, and large-scale disasters with roots in both technological and “natural” realms, we seek to bring STS theories and concepts to bear on these crises, applying them to high-stakes, hands-on disaster situations. Following scholars such as Kai Eriksen and Rob Nixon, disaster can be seen as any material effect–weather event, technological malfunction, or chronic contaminant–that disrupts social and cultural forms to an extent that society can no longer reproduce itself.

In particular, we seek to explore how STS theories and methods might extend beyond academe: How can our work assist first responders, disaster managers, activists, scientists, public institutions, community-based organizations, and vulnerable groups that bear the brunt of effects and responses to disaster? How can we move discussions from technological fixes to the systemic problems that create ubiquitous hazards? And how does this reframing result in new forms or avenues of action? How can STS matter most in disasters?

We welcome traditional papers, workshops, and trainings on topics that may include, but are not limited to, the following:

• comparisons of genres of disaster and response via STS, especially between the global north and south

• new ways to define, identify, and gather data on/with vulnerable populations that open novel avenues of response

• ways to conceptualize and deal with unpredictability, risk, and uncertainty

• the politics and techniques of mitigation versus adaptation to disasters

• how to collaborate between STS scholars, scientists, and a plethora of first responders

• alternative approaches to data collection, publication, engagement, and outreach

• means to collect and share data across multiple groups of experts and publics