Negotiating informality and urban resilience: implications for equity
Bibliographic record
Abstract
Informality is a distinguishing characteristic of cities in the Global South and is strongly associated with urban inequality. Yet, in pursuing resilience, urban resilience strategies and planning have yet to grapple with the role of informality in social-ecological dynamics, resulting in incomplete representations of the reality of these cities’ socioeconomic and demographic diversity. Neglect of informality has significant, but uncertain, implications for equity in resilience planning. In this paper, we conceptualize the complex, dynamic urban systems in southern Africa as emergent from the interdependent interactions between formally recognized and so-called “informal” institutions, economic activities, and social-ecological processes and entities. These interactions generate feedback and emergent outcomes locally and at the scale of the broader urban system, with complex implications for urban resilience, equity, and sustainability. We explore the role of informality in urban resilience in relation to two cases of urban environmental crises: drought in Cape Town, South Africa, and flooding in Lilongwe, Malawi. The cases illustrate how managing resilience at one spatial or temporal scale can mask or generate inequitable outcomes at other scales. The role of informality and its linkages need to be acknowledged for informality to be better incorporated into urban resilience planning, as recognition is often the first step to confronting legal and normative barriers and significant power asymmetries. Informality is a malleable social-political construct, and the actors who control its definition have significant influence over the distribution of rights, responsibilities, and resilience in urban systems. Any strategy to improve social equity in urban resilience planning therefore must address the asymmetries in power that characterize the informal/formal divide. Formally recognized organizations that can legitimately bridge informal and formal spaces play key roles in enhancing procedural, and thus distributive, justice outcomes, as well as in creating the collective capacity to address rapid urban change in the Global South.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".