Networks of (Dis)connection: Mobility Practices, Tertiary Streets, and Sectarian Divisions in North Belfast

Abstract

Long-standing tensions between Protestant and Catholic communities in Northern Ireland have led to high levels of segregation. This article explores the spaces within which residents of north Belfast move within everyday life and the extent to which these are influenced by segregation. We focus in particular on the role that interconnecting tertiary streets have on patterns of mobility. We adapt Grannis's (1998) concept to define T-communities from sets of interconnecting tertiary streets within north Belfast. These are combined with more than 6,000 Global Positioning System (GPS) tracks collected from local residents to assess the amount of time spent within different spaces. Spaces are divided into areas of residents' own community affiliations (in-group), areas not clearly associated with either community (mixed), or areas of opposing community affiliation (out-group). We further differentiate space as being either within a T-community or along a section of main road. Our work extends research on T-communities by expanding their role beyond exploring residential preference, to explore, instead, networks of (dis)connection through which social divisions are expressed via everyday mobility practices. We conclude that residents are significantly less likely to move within mixed and out-group areas and that this is especially true within T-communities. It is also evident that residents are more likely to travel along out-group sections of a main road if they are in a vehicle and that women show no greater likelihood than men to move within out-group space. Evidence from GPS tracks also provides insights into some areas where mixing appears to occur.

Characterizing People’s Daily Activity Patterns in the Urban Environment: A Mobility Network Approach with Geographic Context-Aware Twitter Data

“…Abundant emerging studies have uncovered new insights into individual human activity patterns in the urban environment, using various types of data sources and methods. For example, GPS (Global Positioning System) tracks of residents were used to study daily mobility patterns between two local communities (Davies et al 2019), longitudinal survey data were used to explore the community structures in people's collective activity space (Xi, Calder, and Browning 2020). González, Hidalgo, and Barabási (2008), using mobile phone call data in the form of call detail records (CDR), revealed that trajectories of human movements across the urban space are not random but show a high degree of spatial and temporal regularity.…”

Built environment in programs to promote physical activity among Latino children and youth living in the United States and in Latin America

“…Location‐based data, including global positioning system (GPS) devices and geographic information systems (GIS) data, have proven useful in examining PA in other populations. 51 , 52 , 53 However, the assessment of children's activity places using location‐based data is limited among Latino youth. 54 , 55 The use of such technologies to explore multilevel influences of PA will provide a better understanding of mobility patterns and activity places in Latino and Latin American youth.…”

“…Innovative strategies that examine behavioral patterns and routes of children's daily activities may help in understanding and in the identification of their activity places. Location‐based data, including global positioning system (GPS) devices and geographic information systems (GIS) data, have proven useful in examining PA in other populations 51–53 . However, the assessment of children's activity places using location‐based data is limited among Latino youth 54,55 .…”

The use of GNSS technology in smartphones to collect sensitive data on human mobility practices: Ethical challenges and potential solutions.

“…The Belfast Mobility Project (BMP) has explored the nature, causes, and consequences of sectarian segregation in the historically divided city of Belfast, Northern Ireland's capital city. Whereas most research on this topic has focused on residential demography, mainly using government census data, the BMP investigated how segregation can arise through everyday mobility practices in activity spaces beyond the home (e.g., see Davies et al, 2019;Dixon et al, 2020Dixon et al, , 2022Hocking et al, 2018;Huck et al, 2019). To do so, we have gathered data using a range of methods, two of which we consider here.…”