A Review of Traffic Congestion in Dar es Salaam City from the Physical Planning Perspective
Bibliographic record
Abstract
Traffic congestion is one of the major problems facing Dar es Salaam City and is attributed by a number of factors including rapid population increase, inadequate and poor road infrastructure, city structure, rapid increase in number of cars and lack of physical plan to control city development. The city is already implementing a number of strategies in order to minimize traffic congestion. However, many of the strategies are focusing on improving the capacity of roads in terms of increasing number of lanes, proposing new overpasses and underpasses at the main road intersections and improving public transport. These strategies cannot fully overcome the congestion problems in Dar es Salaam on their own unless efforts are made to redistribute services and community infrastructure. The latter can be achieved through physical planning, which has the potential of influencing trip generation and travel patterns and traffic volume in specific roads. Therefore to minimize traffic congestion in the Dar es Salaam both strategies for improving road capacity, public transport and physical planning solutions ought to be applied together.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".