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HOME > PAST ISSUE > March-April 2004 > Article Detail

COMPUTING SCIENCE

Small-Town Story

Brian Hayes

Modeling Main Street

Threats to the well-being of small-town America certainly seem plausible enough. As the surrounding farmland is drained of population, merchants on Main Street lose their customers. When those businesses close, jobs go with them. The tax base erodes, so that schools and other services deteriorate, causing still more people to move away. The mobility provided by roads and automobiles is another often-cited factor. Because people can travel farther for routine errands, local shops find themselves in competition with the Wal-Mart in the larger town up the road.

Figure 1. Distribution of towns and cities . . .Click to Enlarge Image

Some of the same developments that put small towns in jeopardy, however, might also sometimes work to their benefit. With all those millions of people leaving the farm, a few might be expected to settle in nearby towns; after all, not every former farmer goes off to Silicon Valley to be a dot-com entrepreneur. Improvements in communication and transportation could also cut both ways; people can live farther from their work and may be enticed by outlying villages. Jobs themselves have also diffused beyond the urban core; thousands are employed in places like Georgetown, Kentucky, and Dodgeville, Wisconsin. Even cultural attractions are no longer so centralized; you can live in the sticks and still get to the multiplex. And market economics is surely at work: A four-bedroom house with Victorian gingerbread trim is more affordable in a Minnesota village than in Boston or San Francisco. Finally, there is the indefinable matter of preferences: Even though most of us now live in metropolitan areas, opinion polls indicate that a majority would prefer rural or small-town life.

A coherent interpretation of all these conflicting trends and forces is not something that's likely to emerge from casual computer modeling. Rural sociologists have been striving to understand the situation for 50 years and more. (In particular, I would call attention to the work of Glenn V. Fuguitt of the University of Wisconsin at Madison, and his students and collaborators.) In spite of extensive fieldwork and careful analysis, there is no consensus about what's in store for America's small towns, and there is no predictive theory.

Although computer simulations will not explain human settlement patterns, perhaps such models can reveal something about what needs to be explained. There may be murky psychological forces at work, but before invoking them it would be useful to know whether any of the observed patterns of migration might be accounted for by simpler mechanisms. An analogy from animal behavior comes to mind: the ant graveyard. Some species of ants tend to gather all their dead in one place, a practice that might seem to require considerable planning and organization. But simulations show that a simple two-part rule will suffice: If you see a dead ant and you're not already carrying one, pick it up; if you see a dead ant and you are carrying one, put yours down near the other. The rules that govern human decisions about where to live are surely not as simple as these, but it's worth seeing what can be accomplished with the most obvious algorithms.








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