Urban regeneration initiatives require a deep understanding of urban challenges, including both physical and social dimensions. Previous research often relies on aggregate analyses of the studied sample, summarising the population's evaluations into average values. However, this approach risks overlooking the social segments within a community and averages out any polarisation of assessments. This research proposes a preliminary cluster analysis approach to investigate the nature of values and challenges the limitations of previous studies. The methodology aims to first identify latent subgroups within the sampled population and then characterize their evaluations. The investigation is guided by two hypotheses: the first predicts convergence of evaluations by segments of the population, while the second predicts divergent opinions. In this case, it is important to consider the synthesis carefully, because the average synthesis reports only one orientation. The study stress-tests the methodology. It takes into account the data set previously studied by Micelli and Giliberto (2023) on the Piave neighbourhood.

Polarisation vs Homogeneity: Unveiling the Heterogeneity of Evaluations for Urban Regeneration

Giliberto G.
2024-01-01

Abstract

Urban regeneration initiatives require a deep understanding of urban challenges, including both physical and social dimensions. Previous research often relies on aggregate analyses of the studied sample, summarising the population's evaluations into average values. However, this approach risks overlooking the social segments within a community and averages out any polarisation of assessments. This research proposes a preliminary cluster analysis approach to investigate the nature of values and challenges the limitations of previous studies. The methodology aims to first identify latent subgroups within the sampled population and then characterize their evaluations. The investigation is guided by two hypotheses: the first predicts convergence of evaluations by segments of the population, while the second predicts divergent opinions. In this case, it is important to consider the synthesis carefully, because the average synthesis reports only one orientation. The study stress-tests the methodology. It takes into account the data set previously studied by Micelli and Giliberto (2023) on the Piave neighbourhood.
2024
9783031746789
9783031746796
Cluster Analysis
Opinion Polarisation
Sample heterogeneity
Urban Assessment
Urban Regeneration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/455788
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