Identifying the Influential: Using the PD4SDG database as a proxy for regime formation
Abstract: This project examines the geospatial coverage and network connectivity of entities that have registered voluntary commitments to the United Nations Sustainable Development Goals as published in the Partnership Data for the Sustainable Development Goals (PD4SDGs) database prior to 2018. We seek to measure support for the sustainable development paradigm. We assume that the projects registered in PD4SDGs represent good faith efforts to support the values, norms, and beliefs of sustainable development. However, merely registering a project in a database is not sufficient for regime formation. We will present mathematical models that attempt to quantify the efficacy of these projects toward regime formation and identify factors that inhibit it.
We first look at the geographical coverage of the projects and the entities conducting them. We then perform a network analysis of the topology of the network where two nodes are connected by an edge if they are partners on the same PD4SDGs project. We identify connected components of entities connected (directly or indirectly) through such collaboration. Then, we apply mathematical connectivity metrics such as degree rank, betweenness centrality, cut degree, and pagerank to identify the most important entities in the network.
We observe that the network has one main giant component containing a majority of entities and a corona of smaller clusters with no connection to the giant component. We are specifically looking to identify characteristics of the corona that inhibit network growth and block regime formation.
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