Walking in African Metropolises: the case of Yaoundé
Bibliographic record
Abstract
African cities facing urban disorder have to deal with the exclusion of the poor from motorised movements, conflicts between all the kind of road users and an increased feeling of insecurity explained by pedestrians. This observation, in a context where there is a progressive inclusion of sustainable urban mobility planning, justifies the question of facilitating walking in the city of Yaoundé, the political capital of Cameroon. This paper aims to analyse factors which can lead to adopt walking, by using qualitative data obtained from a stratified random survey of 100 pedestrians, in the districts surrounding the city centre. Through a binary Logit model, we evaluate the quality level of those factors. The main results indicate that pedestrians are inclined to choose walking because of the travel time, the proximity of their destination, the level of security linked to their route, the presence of recreation areas along it and street lighting. On the contrary, higher is the frequency of trips, lower is the use of walking. Les métropoles africaines font face au désordre urbain avec pour corollaires l’exclusion des pauvres des déplacements motorisés, la conflictualité entre les usagers de la route et le sentiment d’insécurité des piétons. Ce constat, associé à la prise en compte progressive du paradigme de mobilité durable, met en exergue la question de la facilité de la marche à pied dans la ville de Yaoundé, capitale du Cameroun. L’objectif de cet article est d’analyser les facteurs qui sont associés à la marche à pied, à partir des données d’une enquête auprès d’un échantillon aléatoire stratifié de 100 individus dans les communes de la première ceinture du centre-ville. A l’aide d’un modèle Logit binaire qui affecte un niveau de qualité aux variables, nous arrivons à montrer que le temps de trajet, la proximité de la destination, le niveau de sécurité attribué à l’itinéraire emprunté, la présence d’espaces de détente et l’éclairage public favorisent la marche à pied. A contrario, la fréquence des déplacements influence négativement le choix de la marche à pied.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".