What affects perceptions of neighbourhood change?

2016 ◽  
Vol 60 (4) ◽  
pp. 530-540 ◽  
Author(s):  
Meghan Gosse ◽  
Howard Ramos ◽  
Martha Radice ◽  
Jill L. Grant ◽  
Paul Pritchard
Keyword(s):  
Neighbourhood Change

Policing gentrification or policing displacement? Testing the relationship between order maintenance policing and neighbourhood change in Los Angeles

Urban Studies ◽  
2021 ◽  
pp. 004209802199335
Author(s):  
Charles R. Collins ◽  
Forrest Stuart ◽  
Patrick Janulis
Keyword(s):  
Los Angeles ◽  
Low Income ◽  
Quantitative Research ◽  
Police Department ◽  
Relative Displacement ◽  
Simultaneous Increase ◽  
Census Tracts ◽  
Order Maintenance ◽  
Neighbourhood Change ◽  
Number Of Citations

Urban scholars increasingly contend that local police departments play a central role in facilitating neighbourhood change. Recent critics warn that ‘order maintenance’ policing and other low-level law enforcement tactics are deployed in gentrifying areas to displace ‘disorderly’ populations. Despite influential qualitative case studies, there remains scant quantitative research testing this relationship, and few studies that evaluate the link between policing, displacement and gentrification. We address this lacuna, drawing on new citation data from the Los Angeles Police Department (LAPD) and employing a measure of neighbourhood change that focuses on the displacement of low-income residents. Examining policing patterns in 978 US Census tracts in Los Angeles over four years, our analysis reveals that tracts experiencing gentrification – defined as the simultaneous increase in non-poor residents and decrease in the number of people in poverty – experience a greater number of citations compared with other tract types. Similar patterns emerge in our analysis of citations that explicitly target homelessness and extreme poverty. In post-hoc analyses, we found that Census tracts characterised by a decrease in the number of people in poverty experienced greater numbers of total police citations and of citations targeting homeless individuals, compared with other tract types. These findings carry important theoretical implications for understanding the divergent manifestations of, and potential mechanisms driving, order maintenance policing. Methodologically, we contend that police citations provide a more precise measure of order maintenance policing compared with previous studies, and that classifying neighbourhoods in terms of relative displacement of residents in poverty provides much-needed interpretive clarity.

scholarly journals A Markov model of urban evolution: Neighbourhood change as a complex process

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245357
Author(s):  
Daniel Silver ◽  
Thiago H. Silva
Keyword(s):  
Markov Model ◽  
Markov Models ◽  
Past Research ◽  
Hierarchical Approach ◽  
Evolutionary Trajectory ◽  
Complex Process ◽  
Trajectories Of Change ◽  
Neighbourhood Change ◽  
The Impact ◽  
Complexity Theories

This paper seeks to advance neighbourhood change research and complexity theories of cities by developing and exploring a Markov model of socio-spatial neighbourhood evolution in Toronto, Canada. First, we classify Toronto neighbourhoods into distinct groups using established geodemographic segmentation techniques, a relatively novel application in this geographic setting. Extending previous studies, we pursue a hierarchical approach to classifying neighbourhoods that situates many neighbourhood types within the city’s broader structure. Our hierarchical approach is able to incorporate a richer set of types than most past research and allows us to study how neighbourhoods’ positions within this hierarchy shape their trajectories of change. Second, we use Markov models to identify generative processes that produce patterns of change in the city’s distribution of neighbourhood types. Moreover, we add a spatial component to the Markov process to uncover the extent to which change in one type of neighbourhood depends on the character of nearby neighbourhoods. In contrast to the few studies that have explored Markov models in this research tradition, we validate the model’s predictive power. Third, we demonstrate how to use such models in theoretical scenarios considering the impact on the city’s predicted evolutionary trajectory when existing probabilities of neighbourhood transitions or distributions of neighbourhood types would hypothetically change. Markov models of transition patterns prove to be highly accurate in predicting the final distribution of neighbourhood types. Counterfactual scenarios empirically demonstrate urban complexity: small initial changes reverberate throughout the system, and unfold differently depending on their initial geographic distribution. These scenarios show the value of complexity as a framework for interpreting data and guiding scenario-based planning exercises.

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