Methodology

The current 15 community types on the American Communities Project map were updated in 2023. They were identified with the help of Michigan State University Political Science Professor Matt Grossman and the school’s Institute for Public Policy and Social Research. The updated typology was guided by a k-means cluster analysis but hand-edited for consistency with the original 15 ACP clusters.

The k-means analysis created 10 clusters with further divisions made among larger clusters based on a selection of measures, including population density, bachelor’s degrees, household income, and racial and ethnic composition.

Three dozen different variables across the nation’s 3,100-plus counties were used in the cluster analysis. The variables included: population over 65, population under 18, Hispanic population (%), white population (%), non-Hispanic Black (%), foreign born (%), English speaking household (%), under poverty line (%), median HH Income, bachelor’s degree or greater (%), unemployment (%), military (%), manufacturing employment (%), service employment (%), sales employment (%), construction employment %, farm/ag employment (%), government employment (%), enrolled in college (%), transportation employment (%), single mom (%), single household (%), married household (%), households with children (%), average family size, same house as last year (%), owned homes (%), vacant homes (%), median home value, total rate of religious adherence, evangelical adherence rate, Black protestant adherence rate, Latter Day Saints adherence rate, population density, total population.

The current breakdown was guided by the original typology created in 2012 by Prof. Iris Hui, which used a similar k-means algorithm that identified like places.

Sources

The majority of the data used to define the types in the ACP came from the U.S. Census American Community Survey, 2016-2020. Data on religious adherence and faith came from PRRI’s 2020 Census of American Religion.