Comment repenser et réaménager les villes africaines au XXIe siècle ? How to rethink and rework African cities in the 21st centuries?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ArgumentaireL'explosion dmographique et l'extension fulgurante des villes africaines, conscutives au phnomne d'urbanisation galopante, provoquent un accroissement rapide des besoins de la population africaine en eau, logement, emplois, espaces publics, etc. Selon les Nations Unies (2014), l'Afrique comptera 1,2 milliard d'urbains en 2050, contre 450 millions aujourd'hui ; sa transition urbaine s'effectuera l'horizon 2035 avec 50% de sa population vivant en ville.Ce phnomne induit dans ces villes la naissance et la prolifration des quartiers spontans sousquips, sous-intgrs, la pauprisation, la baisse du niveau des services urbains, la dgradation de l'environnement urbain, l'htrognit des armatures urbaines et une persistance des problmes de spculation foncire (Legay, 2011), si elle n'est pas maitrise.A cela s'ajoutent la dgradation de la voirie urbaine, les problmes d'assainissement, d'approvisionnement en lectricit, de propagation des pandmies telles que le VIH/SIDA, le coronavirus, les changements climatiques en milieu urbain, l'inscurit, et la maintenance des infrastructures.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it