COVID-19 and Modal Shift towards Motorized Two-wheelers in Dhaka, Bangladesh
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
Based on in-depth interviews of 17 key informants in Dhaka, Bangladesh, this paper explores the reasons behind the observed modal shift toward motorized two-wheelers that occurred with the COVID-19 pandemic, along with its implications. Analysis of the key informants’ perspectives revealed that individuals’ inclination towards motorized two-wheelers occurs because of maintaining physical distance, lack of walking and bicycling infrastructure, the high social status associated with motorized two-wheelers, and brand promotion. The implications of this modal shift include increased traffic congestion, GHG emission, and traffic incidents. As interviewees suggest, mass communication, understanding users’ perspectives, and promoting equity concepts are needed for a modal shift towards more sustainable options.
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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 | 0.001 | 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) | 0.004 | 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