The purpose of my small project is to better understand community-serving organization collaboration in the Richmond area. My working research questions are (1) How are community-serving organizations collaborating in the city of Richmond?, (2) Who are the key players?, and (3) Which organizations act as gatekeepers between other organizations? These data were already collected in 2015 at a Community Health Fair in the East End of Richmond.
Through a survey, organizations were asked questions about their interactions with other organizations in the area. Since these organizations were being directly asked questions on their perspectives and interactions with other organizations, this is an egocentric network. Similar to the Carrasco reading from this week, the egocentric approach constitutes the interplay between the organizational social structure and their interaction behaviors with other organizations. Thus, these data will be composed of two levels: the ego-network level constituted by a specific organization’s characteristics and overall network features, and the ego-alter level, constituted by characteristics of each alter (or target node organization) and the ties between the organizations (Carrasco et al., 2006).
There are many questions in the survey that ask about awareness, similarity, previous collaborations, current collaborations, and overall description of relationship to the other organizations. For the small project, I plan to develop current collaboration networks to answer the research questions above. Therefore, the networks I develop will focus on the ego-alter level of data. Unlike the two measures mentioned in the Fu paper (daily contacts the survey respondents have and detailed daily accounts of the contact during a specific time period), I feel that these data will still be able to provide quality edge attribute information, similar to those collected in previous literature that assess community-level organizations (Fu, Yang-chih, 2005).
Projects with similar research questions have collected their data through surveys and interviews. In a recent study performed in Michigan, researchers assessed the network of agencies in local communities that promote healthy eating and lifestyles among populations with limited resources. They categorized the organizations based on the limited-resource audiences they served like K-12 schools, health-related agencies, and low-income/subsidized housing complexes. Once they created these categorizations, they looked at four network structures: communication, funding, cooperation, and collaboration. For my project, I don’t plan to categorize the organizations, but I plan to look at the collaboration network structure similar to the images seen above (An R et al., 2017).
The papers I highlighted last week used measures like degree centralization to assess partner collaboration (Buchthal et al., 2015 & Schoen et al., 2014). I plan to borrow these methods to answer my second research question. Betweenness measures were also used (Buchthal et al., 2015) and will be best to assess my third research question. I plan to build on past research by utilizing similar analytic techniques; however, I will eventually be able to assess more than just collaboration networks, expanding the literature further by addressing awareness, similarity, and overall description of relationship to the other organizations. I hope to further develop these questions by using outcome data to better understand the overall impact these organization networks have on the community.
Looking past this semester, the small and large project, I do have some long term goals. Once we can analyze these 2015 data and understand collaboration structures at that time, perhaps we can administer the survey again to assess changes in collaboration over time. And, if we are able to assess outcome data with these network structures, we will be able to provide valuable information to these organizations, allowing them to understand how to best collaborate with others to achieve optimal community impact.
An, R., Loehmer, E., Khan, N., Scott, M. K., Rindfleisch, K., & McCaffrey, J. (2017). Community partnerships in healthy eating and lifestyle promotion: A network analysis. Preventive Medicine Reports, 6, 294–301. https://doi.org/10.1016/j.pmedr.2017.03.007
Buchthal, O. V., & Maddock, J. E. (2015). Mapping the possibilities: Using network analysis to identify opportunities for building nutrition partnerships within diverse low-income communities. Journal of Nutrition Education and Behavior, 47(4), 300–307.e1. https://doi.org/10.1016/j.jneb.2015.03.002
Carrasco et. al. 2006. “Collecting Social Network Data to Study Social Activity-Travel Behaviour: An Egocentric Approach.”
Fu, Yang-chih (2005). “Measuring personal networks with daily contacts: a single-item survey question and the contact diary”
Schoen, M. W., Moreland-russell, S., Prewitt, K., & Carothers, B. J. (2014). Social Science & Medicine Social network analysis of public health programs to measure partnership. Social Science & Medicine, 123, 90–95. https://doi.org/10.1016/j.socscimed.2014.10.057