Illuminating informal cross-border trade in processed small pelagic fish in West Africa
Bibliographic record
Abstract
Abstract Trade in processed small pelagic fish and informal cross-border trade (ICBT) are linked to livelihood activities in West Africa. Although these fish products are being traded informally in West Africa, research on this topic is limited. This study builds on a multi-partner supported ‘FishTrade’ initiative in Africa to illuminate the volume and value of informal fish trade across the Ghana–Togo–Benin (GTB) borders, and the socio-demographic determinants supporting participation and profitability in this trade. We used a structured survey and focus group interviews to obtain data from women fish traders, who handle the entire fish trade in three major Ghanaian markets where ICBT activities are concentrated. Our results showed ICBT across these borders constitutes significant economic and livelihood potential, estimated at about 6000 MT in volume and US$14 million in market value per annum. Furthermore, socio-demographic factors, such as fish traders’ years of experience and membership in an unofficial market cooperative, positively influence participation and profitability, but access to market information negatively affects participation. However, geographical distance, large household size and access to micro-finance negatively affect ICBT profitability. Our findings illuminate that consumers’ purchasing power, fish taste and preference, ICBT’s economic opportunities and a shared heritage and connection significantly influence this form of trading along the GTB borders. We conclude that ICBT in these small pelagic processed fish represents untapped potential for local livelihood and highlight the need for further research on this topic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".