Bibliographic record
Abstract
Africa is urbanising faster than any other continent. The stupendous pace of urbanisation challenges the usual image of Africa as a rural continent. The sheer complexity of African cities contests conventional understandings of the urban as well as standard development policies. Lingering between chaos and creativity, Western images of African cities seem unable to serve as a basis for development policies. The diversity of African cities is hard to conceptualise-but at the same time, unbiased views of the urban are the first step to addressing the urban development conundrum. International development cooperation should not only make African cities a focus of its engagementit should also be cautious not to build its interventions on concepts inherited from Western history, such as the formal/informal dichotomy. We argue that African cities are more appropriately regarded as urban grey zones that only take shape and become colourful through the actors' agency and practice. The chapters of this special issue offer a fresh look at African cities, and the many opportunities as well as limitations that emerge for African urbanites-state officials, planners, entrepreneurs, development agencies and ordinary people-from their own point of view: they ask where, for whom and why such limitations and opportunities emerge, how they change over time and how African urban dwellers actively enliven and shape their cities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.176 | 0.137 |
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; both teacher heads agree on what is shown here.
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".