Factors Influencing Private Vehicle Users' Transition to Sustainable Transport Modes for Enhanced Environmental Sustainability in Indian Context
Bibliographic record
Abstract
Air pollution due to vehicular emissions poses a significant environmental and public health concern, contributing to climate change and premature mortality.This study aims to evaluate the perceptions of private vehicle users regarding their contribution to air pollution and their willingness to adopt sustainable modes of transport.In regards to high congestion, poor condition transport modes, poor pavement condition, heterogeneity modes of transport etc., Kolkata, the third largest city in India, is suffering from critical air pollution due to traffic.A structured questionnaire was used to collect from the private vehicle users on perceptions of air pollution along with their commuting behaviors towards public transport.Principal Component Analysis (PCA) was used in order to identify the key underlying factors influencing their perceptions.The results revealed four major components: Health awareness of Pollution Effects, Motivation for Sustainable Transport, Policy and Responsibility Awareness, Perception of Emissions and Information.This study provides valuable insights towards vehicular emissions through promoting sustainable transport, and mitigating the adverse effects of air pollution on public health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".