‘Does Africa not deserve shiny new cities?’ The power of seductive rhetoric around new cities in Africa
Bibliographic record
Abstract
This paper explores the emerging new master-planned city-building trend on the African continent. Situating our research within urban policy mobilities literature, we investigate the ‘Africa rising’ narrative and representation of Africa as a ‘last development frontier’ and ‘last piece of cake’, an imaginary that provides fertile ground for the construction of new cities. Building upon research on the practices of ‘seduction’ that facilitate urban policy circulation, we argue for the relevance of critically examining elite stakeholder rhetoric to understand the relative ease with which the new city development model is being promoted in Africa. We investigate the enablers, advocates and boosters of new cities, represented mainly by states, corporations, non-profits and consultants to render visible the complex networks of relations and private interests that support and enable the creation and circulation of the new cities model in Africa. We also analyse the pervasive ‘right to development’ argument among African elites, which precludes criticism of new city ventures and circulates problematic assumptions about modernity and development. We conclude by discussing how stakeholder rhetoric limits the range of urban visions that are put into circulation and mobilized for Africa’s urban future.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.032 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| 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".