Effects of the COVID-19 lockdown on the livelihood and food security of street food vendors and consumers in Nigeria
Bibliographic record
Abstract
Nigeria's local food economy was affected by state-imposed restrictions to curb the spread of COVID-19 in communities. Street food vendors and consumers are among local food system actors impacted by such restrictions because their livelihood and food security are contingent on daily operations on the street. Informed by a descriptive qualitative approach, we interviewed 31 street food vendors and consumers who shared their experiences on how the lockdown impacted them. Vendors reported various impacts, including losing income, customers, customer trust, and social connection. Street food consumers reported difficulties meeting their food needs and developing multiple coping strategies, including cutting back on fruit and vegetable consumption and food sharing. Both vendors and consumers would like to see measures put in place to allow them to operate safely in a future lockdown event. This study is timely as the country strives to balance human and economic health amid the pandemic. Key words: Street food vendors and consumers, livelihood, food security, COVID-19, Nigeria.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".