The urban transport challenge in India: <i>Considerations, implications and strategies</i>
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
Motor-vehicle activity is growing rapidly, and causing a wide range of adverse impacts, in Indian cities. Although the poor benefit the least from motor-vehicle activity, they bear the brunt of its impacts. The need to meet this and other urban challenges grows ever more urgent, but Indian cities face constrained resources. The urban transport challenge is one of meeting growing mass mobility needs while minimising negative impacts, given the realities of the context. The factors that contribute to the urban transport challenge, and the constraints that affect the ability to address the problem, are first discussed. The transport needs and priorities, in particular of the poor majority, are highlighted. The importance of adequate infrastructure for non-motorised modes and public transit service is justified, based on these needs and priorities, and contextual capabilities and constraints. Finally, the paper proposes some strategies for addressing challenges with respect to these modes.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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