Note: I will be taking the second module and working on this analysis in coordination with the Feinstein International Center at Tufts Friedman School of Nutrition.
Background: SNA in the development context
Over the past decade, the concept of community-based
development (CBD) has gained traction in the development field, with the goal
of “advocat[ing] community participation in decision-making and management.”[1]
In parallel, Social Network Analysis (SNA) has begun to be seen and utilized as
a tool for monitoring and evaluating capacity building interventions, under the
premise that distributed networks can adapt more flexibly than hierarchically
organized interventions to emerging opportunities and challenges in their
environments and combine talent and resources in new ways to support
innovation.[2]
Humanitarian and development organizations have realized the
potential of SNA to enhance their program implementation.[3]
Oxfam and the International Rescue Committee (IRC), for example, have published
handbooks on how to use SNA methodology in development work, such as Oxfam’s
NGO Guide to Social Network Analysis and the IRC’s Social Network Analysis
Handbook.[4]
Furthermore, SNA is increasingly being used by development
organizations in the field. In its “Budikadidi” development program[5]
in the Kasai province of the Democratic Republic of Convo, Catholic Relief
Services (CRS) employs a strategy of leveraging existing social networks in
villages by empowering “dynamic” individuals to form groups which CRS then
works through to build skills and deliver resources in its programming.
Is leveraging existing social networks enough?
While CRS’s strategy of utilizing existing social networks
to enhance delivery of development programs holds much promise, the potential
marginalizing effect of such an approach has not been fully considered. When
dynamic individuals are empowered by development agencies to lead local-level
change and innovation, they can become “gatekeepers,” or determiners of who in
the village can or cannot reap the benefits of the project.
Accordingly, CRS should analyze the preexisting and
resultant social networks of villages partaking in these projects to determine
the characteristics of inclusion versus exclusion from project activities and
the corresponding network position of these individuals. A fuller assessment of
the gap between “dynamic” and “whole village” networks will expose the challenges
and potential consequences of leveraging existing networks, and uncover
opportunities to improve inclusion in project activities.
How can SNA help shed light on the program’s impact?
SNA can help answer these questions by helping to visualize
and quantify the reach of the CRS’s efforts through its empowerment of
“dynamic” individuals. SNA can also help shed light on those excluded from the
network and enable the development organization to tweak its approach to better
reach the full village.
Methodology
The networks to be analyzed are two villages in the Kasai
province of the Democratic Republic of Congo (DRC).
The SNA will use data from two surveys conducted by the
Feinstein International Center (FIC), part of Tufts University’s Friedman
School of Nutrition. The surveys ask about 330 adults from one village and
about 230 from another village to name the four people in the village they
interact with the most (exact question to be clarified by FIC), and includes
attributes for the individuals.
The SNA will examine the existing networks led by “dynamic”
individuals empowered by the development program, as well as the whole village
network to identify individuals isolated from the “dynamic” networks and
therefore excluded from the benefits of the development program.
Oxfam’s and the IRC’s SNA handbooks suggest looking at the
following network measures when trying to manage and mitigate risks in
international development implementation:
§
Dependency – Is the
network highly dependent on a single actor or funding source? This could create
bottlenecks and/or sustainability concerns.
§
Dysfunctional / Conflicting
Relationships – Are there certain key broken relationships that impede the
entire network?
§
Marginalization – Are
there attributes that correspond with exclusion or marginalization in the
network? Analyzing the structure of the network may help uncover the reasons
for marginalization and help overcome it.
§
Like-me Relationships
– To what extent is the network homophilous vs. heterophilous? How might this
impact the goals of the development program?
§
Structural Challenges
– Is the network overly centralized? Is there a structural split in the
network? Is the network too diffuse?
§
Critical Relationship
Building – Are there actors that are not currently connected that could
have a positive and significant influence on the network if connected?
§
Tap into Under-Utilized
Support – Are there actors very positive about your mission but who have
not been given a key role or have sufficient voice? Consider empowering these
actors to have a more central role.
§
Building Networks within
the Network – Consider building coalitions to raise the voice and influence
of people on board with the development mission.
In looking at the CRS data, we can use SNA to identify which
centrality measures are associated with participation in the development organization’s
activities. To this end, it will be interesting to compare indegree centrality
of the “dynamic individuals” identified by the development agency versus other
individuals in the network. Additionally, betweenness and eigenvector can help
illuminate the potential bridging individuals in each village who could turn
the “dynamic” network into a whole village network.
Looking at whole network measures will help us identify
pre-existing patterns of relationships in the village. The E-I indices of
different attributes, for example, will show the extent of heterophily vs
homophily, or whether individuals tend to gravitate towards “like” individuals.
We can also use SNA to better understand those excluded from
the “dynamic” networks by analyzing the common attributes of isolates and how
they compare to those of individuals in the “dynamic” network.
Finally, we can use Clique analysis and Newman Girvan to
identify pockets of strong connections in the network. This may help identify
clusters of resources that could be better spread across the full network,
and/or opportunities for the development agency to tailor activities and
resources to the attributes and interests of particular groupings.
What’s next?
This SNA will be be incorporated into a series of published articles by the FIC aimed at analyzing and refining CRS’ “social networks” strategy to ultimately improve
the reach of their development programs in the DRC.
One potential limitation of this project may be the timing
of the surveys. If the surveys were conducted after implementation of the CRS
program, it will be difficult to gage the extent to which networks existed prior to the project or were formed, morphed, or grew as a result of it.
In the future, looking at the difference between
pre-existing and post-project networks could shed light on the impact of the
development programs on the nature and strength of village networks, rather
than just using networks as a vehicle for program implementation.
Nonetheless, analyzing CRS’ “dynamic networks” strategy will
not only help improve and refine CRS’ approach, but will illuminate the vast potential
for SNA in the development and program implementation fields.
[2] Faulkner,
William & Nkwake, Apollo. (2017). The potential of Social Network Analysis
as a tool for monitoring and evaluation of capacity building interventions.
Journal of Gender, Agriculture and Food Security. 2. 125-148. 10.19268/JGAFS.212017.7.
1 comment:
Wow, Abby, what a great project! There seems to be a good fit between your interests and those of your partners at Feinstein and CRS. Rather than go into detail here, let's talk about this, as I have both some ideas and some questions that may help guide your work. Suffice it to say, this could be a groundbreaking piece of work that all of you will be proud of--but it will indeed take some work. Looks like you're ready for it!
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