Analysis of Liquefied Petroleum Gas (LPG) Shortage in Ghana: A Case of the Ashanti Region
Bibliographic record
Abstract
Liquefied Petroleum Gas (LPG) is increasingly becoming the preferred choice of fuel in the world. The increase in patronage could be attributed to its affordability, efficiency and environmental friendliness. Like other energy sources, there are challenges that impede the smooth supply of LPG resulting in shortage. Several factors are involved which ultimately affects the efficiency of the entire Supply Chain system. The perennial LPG shortage in Ghana is an uncomfortable experience that needs urgent attention. Therefore, the study seeks among others to investigate the magnitude of noted disruptions that contribute to the shortage of LPG and the extent to which the LPG usage categories influence the length and frequency of shortage. A survey methodology was deployed for a total of 35 LPG retailers and 120 consumers in the Ashanti Region of Ghana. Results of the study indicated that the Technical and Transportation disruption was ranked by retailers and consumers as major factors that disrupt the supply of LPG. Analysis carried out revealed that the frequency of LPG shortages experienced by consumers depends on the categories of usage, whilst the consumers' experiences of the duration for LPG shortage are rather independent on the categories of usage.
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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 | 0.000 | 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 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".