Value Chain Governance of Malawi’s Artisanal Fisheries: A Case of Oreochromis Species
Bibliographic record
Abstract
Value chain governance refers to the relationships among the buyers, sellers, service providers and regulatory institutions that operate within or influence the range of activities required to bring a product or service from inception to its end use. This paper analyses value chain governance in the Oreochromis species (Chambo) value chain. The establishment of value chain governance is likely to lead to improvement in the management of Chambo value chain. The paper examines the different marketing strategies, the opportunities, challenges, the upgrading strategies and the nodes that are along the Chambo value chain. Using empirical evidence, chi-square had a value of 0.154 with an asymptotic significance of 0.926, indicating lack of evidence that value chain stages of Chambo in different strata were not the same. Underrating any stage along the chain has negative economical implications considering that any stage along the chain is supportive to majority of the people. The actors along the chain must learn to be innovative so that they are able to find suitable methods for marketing their fish. It has also been found that crew members benefit less than the gear owners in the chain rewards distribution. Dealing with marketing and distribution constraints, improvement in the working conditions of fishers may lead fishers to maximize their capability by sustainably exploiting the resource and that may have positive impact to both consumers and retailers. Upgrading is helpful as it reduces chain risks at all levels or stages of the value chain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".