Frozen Fish Markets and Marketing Problems in Ibadan, Nigeria
Bibliographic record
Abstract
This paper examined the performance of the frozen fish markets in Ibadan, Nigeria in terms of price transmission,market margins, marketing costs, and the magnitude of changes in these variables. The study revealed that theaverage retail price for Mackerel is higher than that of Stockfish while that of Stockfish is greater than that ofSadinela. The same pattern is observed for the wholesale prices, marketing costs and net margins. All themeasures used to assess the problems gave the same rank ordering. Power supply is first. This is followed bystorage, spoilage, transport cost, finance and lastly market levies. A high level of refrigeration is required. Henceunstable power supply could result in spoilage or deterioration in the quality and economic value of fish. There isthe need for improvement in the fish market environment in terms of the provision of infrastructures such aselectricity and storage facilities.
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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 | 0.005 | 0.001 |
| 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 | 0.001 |
| 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".