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Demographic Trends in the U.S.: Neighborhoods

The Washington Post opinion writer E.J. Dionne Jr.’s recent column “Where goes the neighborhood?” (August 10, 2014) recognizes America’s changing concept of “neighborliness” and proffers two new books to spur discussion of America’s ideological split: Marc J. Dunkelman’s The Vanishing Neighbor and Paul Robert’s The Impulse Society.

Dionne reports how Dunkelman identifies a loss of neighborly “middle ring” relationships (those who live nearby) as Americans now spend time primarily with groups of similar interests—at the expense of developing an understanding of those with more diverse outlooks. Roberts’ Impulse Society speaks of a “culture driven by impulses” at the expense of family and community.

Dionne points out that both authors are careful not to fall into the nostalgic trap of a rosy bygone era with fewer rights, but still finds value in the neighborliness.

Dionne acknowledges at the end of the column Bill Bishop’s The Big Sort: Why the Clustering of Like-Minded America is Tearing us Apart. Bishop’s book asserts our communities are becoming increasingly less homogeneous at the city and neighborhood level.

In the end then, a return to neighborliness apparently won’t result in greater exposure to a diversity of ideologies as Americans have clustered into like-minded ZIP codes with similar lifestyle preferences.

As Cory Feldman in the 1992 film The ‘Burbs , incidentally, now on Blu-Ray, put it, “There Goes the Neighborhood”.

Or does it?

In 2013, The Washington Post provided a series of maps of the 2012 presidential election illustrating how we are not red or blue (politically speaking), but primarily purple. At the Census tract level and even to the precinct level, most Americans, the article points out, live in communities somewhere in the middle.

Thus, in one view, taking a microscope approach to community finds increasing homogeneity and polarization; whereas in another view, partisanship, while in strong force on the American landscape, is difficult to detect at a geographic scale.

 Maps by Chris Howard: howardmap[1]

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