Characteristics of Pedestrians in Bangladesh Who Did Not Receive Public Education on Road Safety
Bibliographic record
Abstract
The safety of pedestrians, such as workers who largely walk to and from work, has not been given sufficient attention, especially in the area of traffic safety in developing countries, including Bangladesh. Although the National Road Safety Strategy has a very strong emphasis on road safety education and publicity campaigns, the road safety knowledge may not have reached these vulnerable road users who most needed them. Moreover, little is known about the penetration rate of these campaigns and who have benefited or not benefited from them. On the other hand, the developing country, like Bangladesh, is heavily dependent on its Readymade Garment (RMG) workers for earning foreign currency, and walking is one of the major mode of transports of those workers. The objective of this study is to identify those who are not reach by the safety education. Results from a survey of 1020 RMG workers around Dhaka identified several socioeconomic, demographic, travel characteristics and accident experience that affect the most vulnerable segments who are left out of the system. The findings of this study would help the policy makers to arrange necessary road safety education for the most vulnerable cohorts of pedestrians to encourage the continued use of this sustainable mode of commute.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".