Looking beyond the urban poor in South Africa: the new terra incognita for urban geography?
Bibliographic record
Abstract
The past two decades have seen the development of a rich body of scholarship focusing on South African urban settlements. An extensive narrative has emerged on the changing spatialities of the broader urban system, but the representation of South African urban areas remains surprisingly incomplete. The overwhelming majority of research deals with aspects of urban poverty and aims at informing policy and implementation responses that can provide an alternative urban future – with seemingly limited success.The contention in this paper does not challenge the notion that elevated levels of urbanising poverty represent a future development trajectory of the so-called “real African cities” to which scholars like Pieterse refer. However, such an observation requires considerable refinement in the South African urban context. The growing number of urban residents is not necessarily poor. In fact, the number of relatively wealthy, in Africa generally and South Africa in particular, is rapidly expanding. It is the contention of this paper that, while there might be a moral imperative to investigate poor urban lives, there is similarly an empirical and theoretical obligation to investigate beyond the urban poor. The paper argues that the current imbalance in urban scholarship, focusing too heavily on the urban poor, allows the relatively wealthy to reproduce urban spaces as they please, with little scrutiny from scholars and policy makers. It suggests that, as long as we do not take the realities of these “other” urban dwellers seriously, there is little hope of addressing the fragmentation of the urban form and exclusion of the poor so typical of South African cities. Although existing scholarship aims to integrate currently fragmented cities, ignoring those who are not poor could lead urban scholars to implicitly reinforce South Africa's dualistic cities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.013 | 0.036 |
| Scholarly communication | 0.011 | 0.023 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".