Policies are the products of networks of organizations that span the public and private sectors (Laumann & Knoke, 1987). In particular, the past half century has seen an increasing number of network alliances between multiple entities across sectors (i.e. public agencies, legislative offices, non-governmental organizations, and private sector organizations) in the processes of social service policy decision-making and implementation (Salamon, 1995). However, little is known about the different role of network contexts, properties and substructures in explaining connections within the same social service policy domain. Thus, this study will compare two social service policy networks focusing on how and why differently policy connections are shaped.

We will present comparative findings from two social service policy networks where multiple stakeholders are involved: (1) mental health policy network and (2) adult basic education policy network. The mental health policy network data with 37 actors and adult basic education policy network data with 41 actors were collected through semi-structured interviewing in 2001 in 2005, respectively. Both network data were collected in the same state (we pseudonymed “Newstatia”) in the U.S. that has more than 10 cities and an approximate population of 7,000,000. To model the network data, we will use an exponential random graph model (ERGM) – a stochastic technique for modeling social network data (Frank & Strauss, 1986; Pattison & Wasserman, 1999; Robins, Pattison, & Wasserman, 1999; Robins, Pattison, Kalish, & Lusher, 2007) – by employing the Simulation Investigation for Empirical Network Analysis (SIENA) module embedded in StOCNet (Snijders, 2002). The paper will review the existing literature on factors explaining network contexts, properties and structures, introduce the data, examine the points of similarity and difference between the two cases, and conclude with a set of propositions for future research drawn from this initial comparative case study.