Disposable People as Infrastructure? The Livelihood Trials and Tactics of Three-Wheeler Delivery Drivers on Hanoi’s Streets, Vietnam
Bibliographic record
Abstract
The Vietnamese state is envisioning Hanoi as a prosperous, ‘civilised’ capital city with fast, ‘modern’ mobilities and their corresponding infrastructures, including expressways and an elevated railway. Concurrently, slower informal paratransit are increasingly discouraged and marginalised, threatening the livelihoods of hundreds of three-wheeler motorbike delivery drivers. Despite official registration as disabled war veterans, ‘real’ three-wheeler drivers find themselves in an ever more conscribed environment, while other drivers attempting to maintain livelihoods in this way are deemed ‘fake’ by officials and further ostracised. Drawing on conceptual debates regarding people as infrastructure and mobility (in)justice, and ethnographic fieldwork with three-wheeler drivers, I detail how drivers (both ‘real’ and ‘fake’) must negotiate inconsistent policies, a growing discourse that they are obsolete and hence disposable, and new infrastructures incompatible with their livelihoods. Combined, these elements create specific mobility experiences and frictions to which drivers react with subtle and inventive tactics to maintain their rights to the city’s streets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".