Assessment of the Socioeconomic Aspects of Street Vendors in Dhaka City: Evidence from Bangladesh
Bibliographic record
Abstract
In Bangladesh, informal sector plays a prominent role in terms of their contribution to employment generation and poverty alleviation. Street trading constitutes a significant part of this sector involving street vendors as the key players. Nonetheless the roles of the vendors are ignored and their vulnerable condition is never emphasized. This paper tries to investigate the present status of different street vendors in Dhaka City with the aim of assessing the socio-economic conditions and business issues conducting a field survey of vendors engaged in fruit, vegetable, tea and other food items selling through in-depth personal interview using 3-Stage sampling method. This Study indicates that poverty, migration from rural area, low education, exorbitant supply of labor and large family size are the major driving forces of carrying out this business. According to this survey, Personal savings is the single most important source of financing the vending business. Selling assets and lending from cooperative society are the two other major sources of financing the business representing the absence of formal credit facilities for these poor street vendors. This article also reveals the importance of social capital in street vending and the excessive work hour of the vendors and lack of opportunities of alternative formal employment evident from their fulltime working status even in the presence of political instability, natural calamity or financial crisis.
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How this classification was reachedexpand
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".