Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)


Public Administration


Saba Siddiki


Collaborative Governance;Computational Analysis;Conflict;Environmental Justice;Network Analysis;Representation

Subject Categories

Public Administration | Public Affairs, Public Policy and Public Administration | Social and Behavioral Sciences


In this dissertation, representation, participation, and conflict are examined in state-mandated environmental justice councils. A novel dataset is constructed from council meeting minutes to explore patterns across these key concepts at the individual-level, meeting-level, and council level over time. The first essay examines how meeting-level factors – such as participant diversity, attributes of the meeting, and context – associate with meeting-level participation measured as different types of communication. This essay builds on participation research in collaborative governance, exploring participation through the lens of communication. Leveraging multiple OLS regressions, associations between meeting-level factors and participation through communication are explored. The results help pull apart the dynamics of two-way communication in public participation, identifying unique patterns of cross-sector information exchange as well as meeting-level mechanisms for engaging stakeholders. These results add nuance to how participation is understood in collaborative fora. The findings of this study are applied to the broader field of collaborative governance. The second essay explores how an actor’s interpersonal relationships (i.e., conflict and reciprocity) and goal advancement (i.e., supporting or opposing a council’s annual objectives) associates with the actor’s participation measured as attendance over time. This essay adds to recent work exploring collaborative governance evolution by exploring the factors influencing sustained engagement in the collaboration at the actor-level. Manual and computational text analysis approaches, along with a Stochastic Actor-Oriented Model (SAOM or colloquially SIENA models), are applied to individual-level data across eight years of meetings. The results identify positive and negative interpersonal interactions are associated with changes in individual attendance, whereas only comments opposing a council’s annual objectives are associated with increases in individual attendance. This suggests ‘who remains at the table’ to make policy decisions is influenced by iterative, individual experiences. The third essay tracks the stated goals of a collaboration over time to explore patterns of participation across meetings to better understand how diverse stakeholders engage over time. In this essay, I leverage Emerson and Nabatchi’s collaboration dynamics to explore the change in participation between a collaboration’s decision to address a policy issue (i.e., shared motivation) and a collaboration’s decision in how the issue should be addressed (i.e., capacity for joint action). Separable temporal exponential-family random graph models (i.e., STERGMs) are used to evaluate the pre- and post-trends in representation, which are then clustered into eight representation patterns using a K-Means Cluster Analysis. By framing policy issue advancement as an event study, I argue the results of this paper suggest there are multiple pre-post trajectories in the council, offering insight into the complex nature of goal identification and action in the collaborative setting. The discussion works to link these results to patterns identified in theory.


Open Access

Available for download on Sunday, June 14, 2026