智慧城市中的知识政治:以英国剑桥市战略性城市规划为例

IF 1.8 Q3 PUBLIC ADMINISTRATION
Data & policy Pub Date : 2021-11-17 DOI:10.1017/dap.2021.28
T. Nochta, N. Wahby, J. Schooling
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引用次数: 4

摘要

摘要本文强调了在未来智能城市的循证决策中建设性地结合不同类型(模拟和数据驱动)知识的必要性和机会。为了解决数据驱动知识假定的普遍性和客观性问题,我们呼吁注意与城市现在和可能的未来有关的知识生产中的“位置性”和“情境性”概念。为了说明我们的论点,我们引用了英国剑桥城市地区战略城市(空间)规划的案例研究。追踪不同的知识生产过程,包括从城市建模中获得的自上而下的数据驱动知识,以及自下而上的模拟社区知识,使我们能够围绕政策证据确定特定于地点的知识政治。研究结果强调了基于证据的城市政策如何从不同“数字”和“模拟”知识之间的互动所产生的竞争、争论、谈判和互补的政治过程中受益。我们认为,研究这些过程有助于建立一个更加多方面、多样化和包容性的知识库,作为政策决策的基础,并有助于提高人们的认识,提高人们对正在进行的城市“智能化”的积极参与。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Knowledge politics in the smart city: A case study of strategic urban planning in Cambridge, UK
Abstract This paper highlights the need and opportunities for constructively combining different types of (analogue and data-driven) knowledges in evidence-informed policy decision-making in future smart cities. Problematizing the assumed universality and objectivity of data-driven knowledge, we call attention to notions of “positionality” and “situatedness” in knowledge production relating to the urban present and possible futures. In order to illustrate our arguments, we draw on a case study of strategic urban (spatial) planning in the Cambridge city region in the United Kingdom. Tracing diverse knowledge production processes, including top-down data-driven knowledges derived from urban modeling, and bottom-up analogue community-based knowledges, allows us to identify locationally specific knowledge politics around evidence for policy. The findings highlight how evidence-informed urban policy can benefit from political processes of competition, contestation, negotiation, and complementarity that arise from interactions between diverse “digital” and “analogue” knowledges. We argue that studying such processes can help in assembling a more multifaceted, diverse and inclusive knowledge-base on which to base policy decisions, as well as to raise awareness and improve active participation in the ongoing “smartification” of cities.
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来源期刊
CiteScore
3.10
自引率
0.00%
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审稿时长
12 weeks
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