@article{steelman_nowell_velez_scott_2021, title={Pathways of Representation in Network Governance: Evidence from Multi-Jurisdictional Disasters}, volume={31}, ISSN={["1477-9803"]}, DOI={10.1093/jopart/muab004}, abstractNote={AbstractGovernance systems reconcile diverse interests to enable collective decision-making and action. Questions related to representation in the governance of networks are addressed in the literature; underexplored is the empirical variation in governance arrangements and pathways of representation. Complex, multi-jurisdictional disasters provide a robust theoretical and empirical context in which to investigate network governance pathways due to the tensions between democratic principles of representation and the need for timely, expert-informed response actions. In this article, we address three questions related to network governance, representation, and complex disasters: what governance structures allow for a representation of diverse interests? What governance structures provide a perception of voice to key affected parties? And where do we see variation in the kinds of structures that give voice to these entities? Using an inductive, grounded theory approach along with mixed methods that include case studies, interviews, and archival data in the form ICS 209 incident reports, we provide evidence from 10 of the most jurisdictionally complex wildfires that took place in 2017. In doing so, we introduce the distinction between macro and micro structures of network governance for understanding more precisely the pathways by which representation occurs and how representation functions in disaster networks. There is no singular normative goal when we think about network governance and representation in disasters; rather there are competing contingencies that emerge out of complex contexts. We propose four key propositions to guide further work in this arena.}, number={4}, journal={JOURNAL OF PUBLIC ADMINISTRATION RESEARCH AND THEORY}, author={Steelman, Toddi and Nowell, Branda and Velez, Anne-Lise and Scott, Ryan}, year={2021}, month={Oct}, pages={723–739} }