Do Neighborhood Contexts Influence the Prevalence of Neighbor Problems?
Lynda Cheshire (The University of Queensland, Australia), Siqin Wang (The University of Queensland, Australia) and Yan Liu (The University of Queensland, Australia)
Human beings live in a society embedded by intricate networks and relationships with other people, including their neighbors who offer localized interactions at the day-to-day level. While it is expected that neighbors are generally friendly, helpful and respectful of each other’s privacy, in reality, there is considerable variation in the way neighbors perceive and interact with each other. This suggests that neighboring is not an unproblematic social practice, but can be wrought with tensions and conflicts that arise in the context of living in physical proximity. Neighbor annoyances over noise, pets, parking, fences or trees can undermine one’s sense of home as a place of enjoyment, privacy and autonomy, while disputes can escalate into criminal behavior involving damage to property, intimidating behavior and physical harm.
Of course, the distribution of neighbor problems is not even across urban areas, but depends on the type of neighborhood people live in. Individual characteristics such as age or income might explain how a neighbor's conduct is subjectively construed as a nuisance, but the dynamics and sorting mechanisms of urban capitalist development drive certain social groups into certain types of neighborhoods where the odds of experiencing neighbor problems are enhanced or reduced.
In our UAR article, “The problems with neighbors: An examination of the influence of neighborhood context using large scale administrative data,” we examined neighbor problems as manifest in reported complaints to a local municipality in Australia—the Brisbane City Council—to understand how neighborhood features affect the likelihood of neighbors experiencing problems with each other. The complaints dataset was obtained under a confidentiality agreement, and contains 130,342 records of complaints to council in 2016, including those pertaining to problems generated by neighbors. Using a spatial data mining approach we identified 79,999 valid records of complaints between neighbors which were then classified into four broad types according to the nature of the problem reported: animal-related; building construction-related; property management-related; and health and amenity-related problems. We then propose five hypotheses around the contribution of neighborhood social-interactive, environmental and geographical mechanisms to the formulation of neighbor problems.
We drew on both compositional and contextual features of the neighborhood to test our hypotheses using regression models, while controlling for contacting propensity – the willingness of a resident to contact a city government to address problems. Our models correctly predicted that 72.6% of the city’s neighborhoods have a high likelihood of encountering problems relating to the four sets of issues we identified, although they varied by neighborhood type. We found that residential heterogeneity does not appear to play a role in residents’ perceptions of their neighbors as a problem, either due to a ‘benign sense of rubbing along together’ that creates tolerance among difference, or, more straightforwardly, because the neighbor problems generated through increased population diversity are not the kind of problems that are generally brought to a local municipality.
Consistent with previous research, we found that lower levels of socio-economic status are associated with a higher likelihood of experiencing neighbor problems, particularly those around property management issues. We also found that a high rate of residential mobility is positively associated with an increased odds of experiencing all kinds of neighbor problems. When neighborhoods encounter higher levels of residential mobility, local social ties become unstable and expectations for collective life are reduced. Low-income neighborhoods, in particular, can experience residential churn via a range of urban processes that generate the in-flow of low-income arrivals, the exit of more affluent households as their situations improve, and/or policies of social mix that destabilize established social networks. These neighborhoods are also likely to contain a greater proportion of private rental housing, which inevitably fosters residential instability. In addition, neighbor tensions may also arise due to properties being situated on smaller land lots with less green space, or constructed with cheaper building materials that do not attenuate noise. This reminds us that neighbor problems arise as much from poor urban design and construction as they do from any perceived inadequacy to effectively regulate residents’ conduct.
Where residential tenure is significant is in the increased likelihood of neighborhoods with high levels of rental housing to encounter neighbor problems around property management related issues. This may be driven by generalized expressions of tenure prejudice among homeowners towards renters, although since we do not know the individual details of the complainant or the offending neighbor, we cannot be sure that the former is a homeowner and the latter a tenant. Another possibility is that landlords are absent neighbors. If a problem arising from a neighboring rental property reflects the transgression of the landlord rather than tenant, a neighbor who cannot contact the landlord to report a problem might thus resort to a formal authority for remedy.
In summary, our findings indicate that the sources of neighbor problems reside in a combination of the compositional and environmental features of the neighborhood. Our contribution from this paper is threefold. First it exemplifies the use of large-scale administrative data to explore micro-level patterns in the enactment of urban social life. Second, it attends to the everyday and seemingly mundane practices of neighborly life rather than the overt and more public expressions of, and responses to, urban decay and disorder. While neighbor problems around fences, trees or dogs might be a banal, domestic preoccupation, if serious enough, they can undermine one’s sense of home, escalate into criminal conduct and command significant time and resources of local councils, police and court systems. They can also erode trust among neighbors and undermine the capacity of neighbors to collectively respond to threats, such as crime, disasters and public health emergencies. Finally, the ability to uncover the neighborhood factors that contribute to neighbor tensions—concentrated disadvantage, residential instability, poorly constructed dwellings, and a lack of physical buffers between dwellings—provides a starting point for addressing the sources of neighbor conflict and tension. Only then can planners and policymakers design neighborhoods where triggers for conflict are minimized.
Lynda Cheshire is professor of sociology at the University of Queensland. Her research explores the way socio-structural and urban policy changes impact on the way people live and interact in local neighbourhoods and communities, and the effect of these on social conflict, cohesion and sense of home. She has published the findings of her research widely in journals such as Urban Studies, Housing Studies, Journal of Rural Studies and Environment and Planning (A&C).
Siqin Wang holds a PhD in human geography and is a post-doctoral research fellow within the School of Earth and Environmental Sciences at The University of Queensland, Australia. Her research focuses on urban geography, migration, 3D visualisation, spatial analysis and urban modelling. Her publications cover topics including migration and residential mobility, residential pathways, big data application in transport planning, neighbour complaints, and ageing issues in the interdisciplinary field of urban geography and sociology.
Yan Liu is professor of geographical information science at The University of Queensland, Australia. Her research focuses on cities and computational urban science, including urban analytics, modelling and geo-simulation, and the applications of GIS and Big Data analytics in spatial planning, policy analysis and spatially integrated social studies. She is the author of the book Modelling Urban Development with Geographical Information Systems and Cellular Automata(CRC Press, New York, 2009).