Economic Implications of Renewable Energy Transition in Nigeria
Bibliographic record
Abstract
The energy system worldwide is undergoing transition to renewable energy (RE) due to concerns over depletion and environmental impacts of fossil-fuel sources, energy security, as well as the volatile nature of crude oil prices. In Nigeria, the need to support this transition is underpinned by the deplorable state of Nigeria’s electricity sector which is marred by electricity shortage, domination of fossil-fired systems, struggling power infrastructure and bad governmental influences, among others. The transition to RE is to be considered a viable solution to the aforementioned problems because it encourages decentralised generation which makes room to bypass the bottlenecks in Nigeria’s current electricity system. However, the transition to RE in Nigeria has been slow due to policy inconsistencies as noted by the REMP policy document in 2005. In reality, RE transition is complicated because it demands multidisciplinary approach to address social, economic, and environmental issues. Thus, this study is undertaken to analyse the economic implications of RE transition in Nigeria by linking the effect of macroeconomic factors such as investments and energy costs, industrial competitiveness, energy efficiency (EE), GDP changes, employment, income level and standard of living on the progress of transition. Afterwards, the result of the analyses is used to develop a set of criteria useful in measuring the progress of the proposed RE transition. Lastly, some inputs are made towards the sustenance and intensity of the transition process.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".