Browsing by Author "Dor, Graeme"

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    Mapping transit-oriented economic and social impacts of Gauteng’s postApartheid spatiality: an analysis of precarious workers associated with the Casual Worker’s Advice Office
    (2022) Dor, Graeme
    Precarious forms of employment have become a prominent feature of the labour process, with varying factors contributing to workers’ level of precariousness, informed by inherent social, economic, and spatial dynamics. The influence of social and economic dynamics is well researched and understood, yet the influence of spatial dynamics is largely unexplored. The aim of this research wasto explore the spatial attributes and factors that define precariousness, in the context of the post-Apartheid Gauteng region, through a case-based study of the Casual Workers Advice Office (CWAO). Founded in 2011, and based in Germiston, Gauteng, South Africa, the CWAO represents precarious workers, predominantly labour broker workers, providing labour rights-related advice and support to workers spread across the Gauteng City-Region (GCR). Formed out of the recognition that a growing section of the working class is being subjected to new and precarious forms of employment, the CWAO provided an ideal case scenario to assess the influence of Gauteng’s unique post-Apartheid spatiality on precarious workers. To assess this, advanced geostatistical and GIS-based analytical techniques were employed using an exploratory spatial data analysis (ESDA) approach. This necessitated analysis of three datasets composing data from the CWAO, in worker membership details and an accompanying survey, and from the Gauteng City-Region Observatory’s (GCRO) Quality of Life (QoL) 2017/2018 survey. These datasets enabled the identification of spatial patterns, the creation of a spatial regression model and a job accessibility index, which demonstrated the presence and complexity of spatial dynamics associated with the distribution of precarious workers across the GCR. First, the location of CWAO associated workers’ residence and associated workplace was mapped, with findings showing no significant difference in the distance that these workers reside from work compared to respondents from the GCRO QoL survey A geographically weighted regression (GWR) model was then applied given its ability to generate individual regression coefficients as a continuous function across space, providing a valuable measure of spatial heterogeneity. A percentage change increase in model performance of 20% was achieved when compared to a nonspatial regression model, highlighting the effect of spatial heterogeneity across the study area and the importance of adopting spatially weighted variables in predicting employment status, the selected measure of precariousness. In addition, the creation of a job accessibility index, derived from location data in residence and workplace coordinates of precarious workers associated with the CWAO, alongside a net wage after commute (NWAC) layer developed from the GCRO QoL survey highlighted spatially dynamic job accessibility scores across the GCR. Increased job accessibility for areas located centrally within the GCR, corresponding to the economic hub, was contrasted by a less distinct spatial pattern in a NWAC layer, a component of the accessibility index. Nevertheless, the product of the accessibility index displayed a statistically significant association, at a 5% level of significance, with employment status. Overall, the results outlined the complexity of Gauteng’s unique spatiality and the necessity for developing multi-dimensional analyses to better understand the underlying spatial dynamics associated with precarious workers. Defining the spatial conditions that influence workers’ level of precariousness provides the opportunity to implement practical solutions in advice, advocacy work, and organizing strategies to ensure workers’ needs are addressed. The analyses performed in this study have laid the foundation for facilitating future research on the spatial dynamics of precarious workers.