WK-2023-EP-03
Project Leader: Margot Rubins
Spatial Planning, School of Geography and Planning, Cardiff University, UK
Partners:
- Sarah Charlton, Associate Prof., School of Architecture and Planning, University of the Witwatersrand, Johannesburg, South Africa
- Priscila Izar, Post-Doctoral Research Fellow, Centre for Urbanism and the Built Environment, School of Architecture and Planning, University of the Witwatersrand, Johannesburg, South Africa
- Albert Cuthbert Nyiti, Assistant Research Fellow / Assistant Lecturer, Affiliation: Ardhi University, Institute of Human Settlement Studies (IHSS), Tanzania
- Alex Halligey, Research Fellow , Johannesburg Institute for Advanced Study, University of Johannesburg, South Africa
Abstract:
Walking as a mode of transport is unequally accessed and experienced. Intersectional factors of identity such as race, class, ethnicity and gender, to name a few, influence the ways in which walking is practiced and how different people navigate and negotiate the city during the course of the day and night. Although there has been significant work done on gender, safety and walking, less is understood about the way that intersectionality impacts the challenges and experiences of walking, especially in the Global South.
This study proposes a comparative, qualitative study using walking interviews and photography to investigate the daily experiences of walking throughout the 24 hour cycle. The study will take place in three important but diverse cities, Tshwane, South Africa; Dar es Salaam, Tanzania; and Cardiff, Wales. It will examine both pragmatic and technical aspects of walking as a mode of transport i.e. how and why people walk; their access to amenities; and the connections to other modes of transport.
Moreover, the study aims at engaging in the lived experiences of people using walking as a mode of transport. This will give insights into the challenges they face, including different kinds of violence, and the nature of embodied and performative identities. The proposal is exploratory and experimental in nature, with a clear focus on iterative learning and the potential for scaling up.