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A radical proposal: Policy and design to create smaller, smarter cities in the United States.

机译:一个激进的提议:在美国建立更小,更智能的城市的政策和设计。

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摘要

Smart shrinking, as policy intervention for declining cities, has yet to be completely developed in the United States. As a term and concept borrowed from German planning literature, it offers an alternative approach to standard growth-oriented planning models. What it proposes is a radical, yet feasible, paradigm shift in the way that city officials and residents alike view the function of cities. No longer is the city's purpose viewed only as growth machine. Rather, under smart shrinking, cities are viewed as free to tailor urban policies based on actual population projections instead of unrealistic expectations of growth. Smart shrinking provides the means to downsize the physical infrastructure of cities. It rids itself of past negative connotations of decline by focusing on the empowering effects that such a shift offers to cities. What would be labeled as "failure to grow" under growth-centric policies becomes an accomplishment of shrinking under the proposed new paradigm. This thesis investigates and interrogates the history of smart shrinking, the ways in which these policies can be implemented in the US, and the benefits of smart shrinking over growth-oriented planning policies. It uses the cities of Youngstown (Ohio), Leipzig (Germany), and Bradford (Pennsylvania) as case studies.
机译:作为对衰退城市的政策干预,智能收缩在美国尚未完全发展。作为从德国规划文献中借来的术语和概念,它为标准的面向增长的规划模型提供了另一种方法。它提出了一种根本性的,但可行的范式转变,使城市官员和居民都可以看到城市的功能。城市的目的不再仅仅被视为增长的机器。相反,在智能收缩的情况下,城市被视为可以根据实际人口预测而不是对增长的不切实际的期望来调整城市政策。智能收缩提供了缩减城市物理基础设施规模的方法。通过专注于这种转移给城市带来的赋权效应,它摆脱了过去下降的负面含义。在以增长为中心的政策下被称为“增长失败”的东西,变成了在拟议的新范式下萎缩的成就。本文研究并审视了智能收缩的历史,在美国实施这些政策的方式以及智能收缩相对于面向增长的计划政策的好处。它以扬斯敦(俄亥俄州),莱比锡(德国)和布拉德福德(宾夕法尼亚州)的城市为案例研究。

著录项

  • 作者

    Gayley, Rebekah J.;

  • 作者单位

    University of Delaware.;

  • 授予单位 University of Delaware.;
  • 学科 Urban and Regional Planning.
  • 学位 M.A.
  • 年度 2008
  • 页码 153 p.
  • 总页数 153
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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