Assessment of Motorcycle Ownership, Use, and Potential Changes due to Transportation Policies in Ho Chi Minh City, Vietnam
Bibliographic record
Abstract
Although motorcycles are the main mode of transportation in many megacities in developing countries, very little research has been conducted on motorcycle operations and related issues. This paper addresses (1) the empirical analysis of the current status of motorcycle ownership and utilization in Ho Chi Minh City, (2) the estimation of the number of motorcycles used in this city, and (3) the analysis and modeling of different transportation policy scenarios. For (1) and (2), the survey results indicate that on average motorcycle ownership (2.33 motorcycles) is higher than that of working-age people in a family (2.29 people). The total number of motorcycles operating in Ho Chi Minh City is estimated to be almost 2 million fewer than that of registered motorcycles. For (3), the results show that each proposed scenario has its own advantage. The demand management policy, which involves either reducing demand via ride sharing or reducing the number of working days per fortnight to 9, is found to be the only single policy that results in little to no adverse impact on total vehicle trips, emissions, fuel consumption, or revenue.
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 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".