The Effects of Poverty Reduction Strategies on Artisanal Fishing in Ghana: The Case of Keta Municipality
Bibliographic record
Abstract
This paper assesses the level of poverty in Ghana after three decades of successive implementation of numerous poverty reduction strategies including Structural Adjustment Program (SAP) by various governments of Ghana. The Keta municipality in the Volta region, where artisanal fishing thrives, was chosen as a representative sample of the whole country. The authors identified eleven artisanal fishing communities in the selected area using systematic sampling. Data were collected on household consumption patterns. This process was used to determine the profile of poverty using the latest upper poverty line of Ghana and the Greer and Thorbecke (1984) poverty formula. Research findings show that the various poverty alleviation methods implemented over three decades by the Government of Ghana, the World Bank, and the International Monetary Fund (IMF) significantly failed as they have not produced any meaningful effect on poverty reduction in the sample area. Finally, this paper offers further suggestions regarding how this poverty gap may be bridged using alternative methods.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".