The Effects of Pandemics on the Vulnerability of Food Security in West Africa—A Scoping Review
Bibliographic record
Abstract
The purpose of this paper was to show the effects of the Ebola and COVID-19 pandemics on food security vulnerability in West Africa. The methodology is based on a scoping literature review using the PRISMA method. The study showed that food security was affected by the restrictive measures in the different West African countries. In addition, it shows that this region is highly vulnerable to such crises, which can combine their effects with those of other events such as climate change and civil unrest. In both pandemics, all pillars of food security were affected. The effects on urban and rural centers may be very different. The study suggests a better understanding of the differences between rural and urban centers and between men and women and how long-term restraint measures can affect rural areas where agriculture is the main lever for reducing food insecurity. Food security must be seriously considered by governments when implementing restrictive measures during a pandemic. Consideration of health factors alone at the expense of food security can greatly exacerbate health problems and even increase cases of disease.
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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 | 0.010 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".