Authors: Fran Meissner*, TU Delft
Topics: Legal Geography, Migration, Urban Geography
Keywords: superdiversity, visualisation, sequence analysis, migration, immigration status, urban diversity, migration-driven diversity
Session Type: Paper
Start / End Time: 1:10 PM / 2:50 PM
Room: 8210, Park Tower Suites, Marriott, Lobby Level
Presentation File: No File Uploaded
This paper commences with the question what role categorical diversity and taxonomies of difference should play in our efforts to visualise urban superdiversity based on quantitative data. As I have argued in previous work, the analytical challenge of superdiversity is all too often cast as dealing with many variables and categories. While granularity is certainly an issue, taken seriously, the analytical challenge superdiversity poses lies with better understanding complex spatio-temporal dynamics in relation to what has been called a diversified-diversity. The space/time of diversity is thus presumably linked to the governance of diversity a nexus that can usefully be addressed through visual representations. Dynamics and trajectories can be expressed in terms of sequences to show change over time for different migrants living in different urban settings. Sequence analysis and the visual representations it produces can, for example, be usefully implemented to explore if and how immigration status is relevant for where migrants move to and what kind of spatial trajectories migrants follow. Building on those premises this paper draws on a unique register based data-set that allows ‘following’ migrants who arrived via different immigration routes (asylum, work, study, EU free movement) through both space and time. We can thus make visually accessible the diversity of spatial trajectories – operationalised through changes in neighbourhood characteristics - that migrants follow and how those patterns differ between different types of cities. The paper concludes by focusing on how those patterns matter for making sense of diversity dynamics through a superdiversity lens.