The Paradigmatic Exceptionality of New York: Scaffolding a Radical Literary Urbanism

Abstract

Amongst the great American urban centers, Chicago is the city that hosted the emergence and development of the first school of urban sociology in the 1920s. The strongly influential body of work of the so-called ecological urbanism by Ernest Burgess, Robert E. Park, Roderick D. McKenzie, and Louis Wirth is noteworthy for its structural interpretation of the city and the preoccupation with “patterns of regularity” in community formation.1 Chicago was a blueprint urban formation made up of concentric circles, and a “product of nature, particularly of human nature.”2 The city developed akin to a biological organism through adaptation, self-selection, and competition.3 For this reason, the Chicago School came to be known as the proponent of the human ecology approach to urban space, a positivist perspective, which was to dominate urban geography until about the 1970s. If Chicago was the first laboratory for the production of urban theory and critique, then it is suitable to claim that New York City was such a prime laboratory for the radicalization and reformation of geographical thought, in keeping with the “social production of space” and its roots in late capitalism. New York, the borough of Manhattan in particular, is both a paradigmatic metropolis—template for the late twentieth-century, American, and global city—and an exceptional urban space that cannot be restricted to a fixed model of urban development. For this reason, New York is the most suitable location for vital spatial demystifications: a geo-historical account of the city’s “creative destruction” in its transition from a Fordist to a post-Fordist mode of production is also an account of the figurations—as urban myths—which the city has maintained and subverted.KeywordsUrban SpaceCreative DestructionLiterary TextIndustrial MutationCultural GeographyThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.