World-class dreams, marginalized realities: Neoliberal urban governance in the Global South
Bibliographic record
Abstract
This paper examines the lasting influence of neoliberalism on urban planning and policy in the Global South, shaped significantly by the Structural Adjustment Policies (SAPs) promoted by International Financial Institutions (IFIs) during the 1980s and 1990s. These policies introduced key elements such as market-based governance, privatization of state-owned enterprises, the promotion of private property rights, and the weakening of public interest criteria, all of which have become central to urban development processes. Urban governance in Global South cities remains heavily influenced by these IFI-driven policies, with a focus on world-class infrastructure projects that often overlook equity and the needs of the urban poor. These cities increasingly rely on market mechanisms rather than state intervention to allocate scarce resources, further entrenching socio-spatial disparities. Using examples from the water sector in Bolivia and Jakarta, the housing sector in Ghana, urban development in African cities, and emerging urban governance models in India, the paper demonstrates how neoliberal policies have struggled to prioritize socio-spatial redistribution. Instead of mitigating social inequalities, these policies often exacerbate them. The paper advocates for a reimagined urban governance approach that centres on equity and improved access to essential services, underscoring the need to rethink development paradigms in the Global South. • Analyzes the enduring influence of neoliberalism on urban planning in the Global South. • Examines how International Financial Institutions (IFIs) promoted privatization and market-based governance. • Demonstrates how urban policies often overlook equity, deepening socio-spatial disparities. • Draws on case studies from Bolivia, Jakarta, Ghana, and India to reveal systemic challenges. • Advocates for equity-focused urban governance and rethinking development paradigms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.022 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".