Fast Company: The Best Cities Are Ones Where You Can Make Friends

(Originally published at FastCompany.com on May 28, 2013.)

In 1964, the sociologist Melvin Webber suggested the city of the future would more closely resemble Amazon’s random-access warehouses than the canyons of Manhattan. Thanks to the car and its “door-to-door, no-wait, no-transfer, private, and flexible-route service,” Webber wrote, dense urban cores would give way to what he called “community without propinquity”—settlements spread unevenly across the landscape loosely bound together by social networks and freeways rather than sheer physical proximity. The result, he believed, would be unprecedented choice in how and where to live and who and how often to meet face-to-face—effectively anyone, anytime, anyplace.

Webber’s exurban vision quickly came to pass, but it’s taken almost 50 years to quantify the results. In a pair of recent papers, Steven Farber, an assistant professor of geography at the University of Utah, and his collaborators have proposed a new metric to measure the latent possibilities for community in cities without proximity: “social interaction potential.” SIP represents the intersecting slivers of space-time in which any random pair of a city’s residents can meet based on where they live, where they work, and, given those, how long they have to rendezvous.

Drawing on census data, travel times, employment densities, and land-use patterns among other statistics, Farber calculated the SIP of 42 U.S. metropolitan regions with at least a million residents. Unsurprisingly, the largest cities—New York, Los Angeles, Chicago, and Washington—also boast the highest aggregate SIP scores. But once you control for size, all four cities underperform compared to smaller peers. For one thing, their vastness works against them—“super-commuters” to Manhattan, the District, or the Loop head straight home at the end of the day, sharply limiting their opportunities for happy hour.

But long commutes pale in comparison to two other factors: decentralization, which produced the edge cities of the 1980s and ‘90s, and the thin schmear of unchecked sprawl that flourished during the housing bubble. “The impact of decentralization is 20 times stronger than commute times,” says Farber. “It’s far more important to move people spatially to the same place than it is tagging on a few minutes to their commutes.” It would seem Melvin Webber was dead-on when it came to community-without-propinquity (especially in our current age of social media), but dead-wrong about the optimal urban form.

“Our results clearly show that more sprawling regions make it harder and harder for people to have social interactions with each other,” Farber adds. “One of the questions on my mind is the relationship between social equity and disparities in SIP. In American cities, I think there will be a huge disparity between those with and those without an automobile. There will be neighborhoods and communities designed for interaction only with the car in mind.” (They’re called “gated communities” for a reason.) “That’s a risky system to have where our success or social capital is contingent on driving around.”

That’s assuming, of course, that a city’s success and social capital are correlated closely with SIP. The usefulness of the metric depends on linking face-to-face encounters with higher quality of life and economic growth—which, given the rich body of literature on the subject from Jane Jacobs’s The Economy of Cities onward, seems likely.

Farber’s ultimate aim is to use SIP as a tool in shaping urban policy. Given that smaller, yet-compact cities such as Boston and Portland make better use of their potential—they’re populous enough to have SIP, while small enough spatially to enable short commutes to the center—he says: “I think the biggest bang for the buck is intensifying density in urban neighborhoods,” says Farber. “If you work in the center and live close to the center, you may have access to 150,000 people instead of 10,000. From there, the possibilities for interaction increase exponentially.”