Methods: This study used network analysis to examine ties between organizations that receive CDBG funding from 2015 (n=62) to 2019 (n=55), and the neighborhoods they serve, which were defined as census tracts (n=106). Data were extracted from CDBG administrative documents and American Community Survey (ACS) estimates for the study period. Data consisted of CDBG project details, implementing organizations, funding amount, project location, and census tract characteristics. Nodes represented organizations and neighborhoods, and ties represented spatially targeted CDBG projects. Network visualizations and descriptive measures were examined for the bipartite CDBG network and each one-mode organization and neighborhood network. Subgroup analyses were conducted for the one-mode networks to detect network subgroups.
Results: Each network consisted of one large component and many isolates. Between 2015 and 2019, organizations receiving funds decreased from 62 to 55 (M=60.80, SD=3.31), and neighborhoods receiving projects decreased from 78 to 73 (M=75.00, SD=1.74). Organizations served approximately 2 neighborhoods (M=2.63, SD=5.91) and neighborhoods received 1 CDBG-funded project per year (M=1.50, SD=1.41), on average. Neighborhoods received an average of 7 projects across all years (M=7.53, SD=6.19), while 17 neighborhoods received no projects. Thirty-three organizations and 63 neighborhoods received at least 1 project during every program year. On average, 10 organizations entered the network (M=10.25, SD=5.56) and 13 dropped out of the network per year (M=13.25, SD=4.27). Density increased for each network over time. Full network density ranged from .01 to .02, organization network density ranged from .13 to .24, and neighborhood network density ranged from .24 to .46. Funded organizations and organizational isolates declined over time, while the number of neighborhood isolates increased. Subgroup analyses indicated that networks consisted of 3 to 6 distinct communities composed of socioeconomically diverse neighborhoods.
Conclusions & Implications: In contexts of economic and racial segregation, our findings suggest that CDBG funding may connect socioeconomically diverse neighborhoods through organizational project implementation, representing a potential mechanism of information and innovation diffusion across geographically distant neighborhoods. Additionally, our findings suggest that CDBG investments became more spatially concentrated over time, increasing the likelihood of producing community-level changes. Finally, our findings indicate that federally funded community development programs have the potential to produce a largely unexplored byproduct: bridging networks between low- and high-resource neighborhoods.