Townology unpacks the nuance of small town dynamics by assigning a custom personality profile to every town in America.
Project Description
America loves its small towns. In American culture, these places are often held up as the bastion of American values, full of mom-and-apple-pie images like cheery storefronts, quaint homes, and heart-warming community pride. Countless books, movies, and political campaigns have celebrated and capitalized on this classic image of America.
At the same time, many of these small places seemingly do not embody that ideal. Urbanization movements have shrunk populations; economic and industry shifts have left limited job prospects for those who remain. Media often portrays small town and rural areas as backwards-thinking, inhabited by distressed populations. There is a rich complexity present in these small places just as there is in urban, more developed areas. Which of these conflicting images of small town America is more accurate, and for whom?
The Townology project unpacked the nuance of small town America by creating a set of seven town character types, resulting in a unique “personality profile” of every town.
The Townology project aimed to reveal the dynamic characteristics of towns from across various regions of the contiguous United States. This nuance is organized as a set of town types, representing seven unique small town characters in America. The research team then applied this typology set to every small town in America, resulting in a unique “personality profile” of every town. These unique types can be explored, and you can find your town, at townology.sasaki.com.
Research Method
The research process included five steps:
Defining: the team worked through a process to define both “place” and “small,” arriving at the definition of a small town place as an incorporated area or Census-designated place with a population under 50,000, resulting in a dataset of roughly 29,000 places.
Gathering data: using publicly-available data at the county, ZIP, and Census place geographic scales, the team compiled over 150 data metrics for these 29,000 places.
Analyzing data: to refine this dataset, the team selected about 40 metrics that seemed most meaningful according to discourse, grouped them into six thematic indices (Vibrancy, Connectivity, Environment, Adaptability, Diversity, and Quality of Life), removed duplicative effects, standardized the index scores, and identified an appropriate number of clusters to generate.
Developing types: the team iterated through several rounds of k-means clustering analysis to result in the seven unique town types, and then described these types using demographic, economic, and physical characteristics, as well as branded names.
Applying the typology: finally, these unique types were applied to the dataset of small towns to result in a “personality profile” for each town based on how closely that town scored to the idealized type. This means that for every town, the dataset describes how strong of a match it is to the types (e.g., 20% type 1, 30% type 2), identifying not only the town’s primary type but also the other types it closely matches.
Findings
Examination of the resulting typological clusters begins to reveal dynamic patterns and relationships that provide nuance to the American small town. For example, one factor that is often assumed to have a large impact on the character of small towns is the town’s proximity to a major metropolitan area. While there are some trends relating to metropolitan proximity (such as the pattern of urban affluence), a small town’s proximity to large cities does not solely account for the characteristics of that place. Racial divides, for example, are strongly felt across towns irrespective of their proximity to the metropolitan core (with the exception of the American South) and are strongly correlated to multiple other data dimensions.
Furthermore, variation in regional groupings reveals the complexity of regional linkages between towns and their metropolitan core. Regional patterns are evident—for example, towns that match closely to Out West Outpost characteristics are primarily west of the Mississippi, while Shrinking Steads are most strongly distributed throughout the Southeast—but regional location alone also does not fully explain the differences between American small towns. For example, the Midwest region includes a huge variety of town types, primarily Blue Collar Burgs and Provincial Patches, but with many other types mixed in as well.
Similarities across character types, regardless of region or metropolitan proximity, suggest there are sets of shared challenges that towns face throughout the contiguous United States. Essentially, a town in Montana can have more in common with a town in Florida than its local neighbor, despite the two Montana towns sharing a region and similar metropolitan proximity. In the context of planning for the small town, Townology begins to reveal shared characteristics of American small towns so that local planners can look across the United States to places with similar challenges to find meaningful solutions.
Role
I was the research lead for this project, which involved initiating the idea, scoping the proposal, and gathering a team. I guided the team through the nine-month process of problem definition, data analysis, synthesizing narrative, and website development. I was also the primary UX/UI designer and developed most of the website’s front end, relying on a partner developer to create the interactive map portion.