Comparative Analysis of the Profitability of Major Value-added Activities Along the Pineapple Value Chain in Ghana
Why this work is in the frame
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Bibliographic record
Abstract
This study aimed to analyze the profitability of sampled pineapple farmers, processors, and marketers in Ghana, which will help to assess how these actors optimize available resources to generate profits and achieve production efficiency. A cross-sectional descriptive survey design was used with interview schedules as the data collection instruments. The sample size was 320, 66, and 169, pineapple farmers, processors, and marketers respectively. The study found that pineapple production and processing were profitable, but marketing was not. The results showed a significant difference in the profit share of the group actors, highlighting that the profit share of each actor along the pineapple value chain is different. The results also showed that income, capital, and planting materials were the main determinants of farmers' profits. On the other hand, capital, pineapples, and packaging materials were the predictors of processors' profits. While transport, revenue, and loading and unloading costs predicted the marketer's profit. Based on these findings, the study recommended that NGOs and other partner agencies promote the pineapple industry in various ways to reduce poverty by providing credit facilities to actors to increase their productivity, profitability, and sustainability.
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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) | 0.000 | 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 it