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|TITLE||US Gentrification Diagnostic System and Its Implications|
US Gentrification Diagnostic System and Its Implications
Lee Jinhee, Associate Research Fellow
Korea Research Institute for Human Settlements
1. A gentrification diagnostic system sends an early wake-up call to policy makers and ordinary citizens by detecting signals for the occurrence or acceleration of gentrification, based on quantifiable demographical and socioeconomic data.
2. The gentrification diagnostic system has been used for policy-making purposes in the US since the 1970s to diagnose signs of gentrification, predict changes in central residential areas in major cities, and come up with proper countermeasures.
3. Being past information, data stored in the existing diagnostic system has limitations in predicting the future such as its focus on drawing attention to the current situation.
4. The development of an improved diagnostic system, which includes qualitative as well as quantitative data, is needed to ensure the accuracy of future predictions.
1) (Advance prediction of gentrification) The pace of gentrification may accelerate or decelerate according to additional changes in supply and demand dynamics in the neighborhood where public investment projects such as urban regeneration are in progress or planned. As a result, it is critical to predict such changes in advance.
2) (Development of a Korean-style diagnostic system for advance prediction) Unlike the case with the US, commercial gentrification is more pronounced in Korea. It is essential to develop a diagnostic system that puts both past and present into perspective and helps predict potential changes in the neighborhood using qualitative and quantitative data that are directly related to commercial gentrification and displacement.
3) (Continuous efforts to improve the accuracy of a diagnostic system) A diagnostic system allows for an effective, proactive response to gentrification. However, prudent approaches are needed because if the system lacks accuracy, it would negatively influence the policy-making process.
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