Cross examinations of maritime trade disruptions in Africa during COVID-19 pandemic
Bibliographic record
Abstract
This study examined the influence of the disruption of COVID-19 on maritime shipping activities in Africa. Particular attention was paid to the variations in the performance of selected African countries in container ship calls, container throughput, and liner shipping connectivity between 2019 and 2020. Eighteen (18) African countries were selected from all the geographical regions of the continent based on data availability. Secondary data was drawn from records of maritime trade in the publications of the United Nations Conference on Trade and Development (UNCTAD) (2019, 2020, and 2021) as well as World Bank Development Indicators for the selected countries. Explorative data analysis was used to organize and present the data. Results showed that the North African region alone recorded an improved percentage of container ship calls in 2020 than in 2019. Results by individual countries showed that Ghana recorded the highest positive increase in ship calls in 2020 from her record in 2019. In addition, Morocco, recorded the highest container throughput in 2020 than the record in 2019 while all the countries exhibited a winding record of liner connectivity between the last quarter of 2019 through the last quarter of 2020. The study concluded that the disruption of maritime activity by the COVID-19 pandemic had a mixed impact on African countries’ performance. However, Africa has the potential to be more resilient to unforeseen shocks and become competitive if it is more integrated into the global supply chain and deploys modern and efficient technology and innovation to the shipping business more than it ever did.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".