Measuring Social Capital
One commonly used measure of social capital is the Rupasingha, Goetz, and Freshwater Index (also known as the RGFI or the Penn State University Social Capital Index; Rupasingha, Goetz, & Freshwater, 2000). The RGFI is a county-level measure of social capital with a well-documented relationship to a range of community health indicators (Lee & Kim, 2013). To create the index, the authors examined proxies of social capital for which data are available, with a focus on formal associations and relationships such as the number of civic organizations in a county. However, one concern about the index is that it underestimates the amount of social capital in counties with large populations of people of color.
To identify more inclusive approaches to measuring social capital, the Health Impact Project, a collaboration of the Robert Wood Johnson Foundation and The Pew Charitable Trusts, commissioned researchers from University of Minnesota Extension to develop an equity-informed, county-level social capital index called RGFI+. This index includes a broader set of organizations where informal socializing activities are likely to occur, including barber shops, beauty salons, manicurists, and coffee shops. The researchers then examined the extent to which the RGFI+ captured more social capital than the original RGFI in counties with large populations of people of color, and how it related to county-level health outcomes.
The RGFI was originally published in 2000 (Rupasingha, Goetz, & Freshwater, 2000). Its authors are economists, so the original intent was to examine the role of social capital in county-level economic development. To create the index, the authors used County Business Patterns data, compiled by the Census Bureau, which includes an extensive set of variables representing membership organizations at the county level. They reasoned that associations such as civic groups, religious organizations, sports clubs, labor unions, and political and business organizations allow for communities to directly interact and collaborate. Their dataset included the county-level number of the following establishments: (a) civic organizations; (b) bowling centers; (c) golf clubs; (d) fitness centers; (e) sports organizations; (f) religious organizations; (g) political organizations; (h) labor organizations; (i) business organizations; and (j) professional organizations.
The authors also included several other county-level proxies for social capital: (a) the response rate for the Census Bureau’s decennial Census of Population and Housing, (b) the percentage of voters who voted in presidential elections, and (c) the number of non-profit organizations obtained from National Center for Charitable Statistics. They used principal component analysis to create a single index out of these variables.
One deficiency in the RGFI is that it excludes social capital-producing organizations that are more prevalent in communities of color and led by women. For example, some research suggests that golf courses, one of the organization types included as a proxy for social capital in the RGFI, is not perceived to be very inclusive of people of color or women (Rosselli, Cunningham and Singer, 2017). In addition, third places (locations other than the home and workplace) such as churches, cafes, clubs, public libraries, bookstores, and parks, are likely key venues for social capital creation. Sociologist Ray Oldenburg argued in The Great Good Place that third places impact civil society, democracy, civic engagement, and people’s sense of place. Yet, many such venues are not included in the RGFI because they are for-profit businesses.
To capture the key role of these organizations, the RGFI+ includes data on beauty and barber shops, nail salons, and coffee shops — places where informal socializing takes place.
Why Build on the RGFI?
There are many ways to measure the social capital assets in communities of color more comprehensively and equitably, but this research builds on the RGFI for several reasons.
Modifying an index based on secondary data is more feasible than collecting primary data. Much of the social capital research has been based on primary sources of data—such as the 2000 social capital benchmark survey conducted by the Harvard University Saguaro Seminar, associated with the political scientist Robert D. Putnam—but this is extremely expensive and labor intensive.
In response to these limitations, several researchers have constructed measures of collective social capital based on secondary data sources, such as administrative records and official statistics. For example, the number of civic organizations within a community can be used as a measure of social capital because these organizations can indicate strong bonds and low-cost relationships that can impact a variety of quality-of-life factors such as health.
County-level data is preferable to state data. Secondary data sources have been used to explore social capital at both the state and county levels in the United States. County-level measures are more useful from a public health perspective because they can be used to identify more targeted interventions. Ideally, secondary data would be analyzed at even more granular levels, such as census tracts or ZIP codes, but not all data sources are available for these smaller units.
The Differences Between RGFI & RGFI+
Compared to the RGFI, the RGFI+ documents stronger social capital levels in communities of color, suggesting that the original index is underestimating the amount of social capital in some counties.
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