Renewable Energy Research in Africa: A Bibliometric Review (1979-2022)
Bibliographic record
Abstract
This paper presents a bibliometric analysis of scientific research on renewable energy in Africa, a rapidly growing field driven by the need for sustainable and accessible energy solutions.It highlights Africa's role as a hub for renewable energy innovation, with local researchers collaborating with global institutions to address the continent's unique energy challenges.This synergy is enhancing energy access in African communities and contributing to the global advancement of renewable technologies.The study meticulously examines 3,109 scientific publications from the Scopus database, spanning from 1979 to 2022.It analyzes the evolution, geographical distribution, and impact of these publications, with a focus on international collaborations and scientific output.Findings indicate that South Africa leads in productivity with 962 publications and hosts the top affiliating institutions in this domain.The study also reveals an exponential increase in renewable energy research, particularly from South Africa, the United States, and the United Kingdom, emphasizing the need for more collaborative efforts and knowledge exchange globally.This analysis provides critical insights into the current landscape of renewable energy research and pinpoints areas ripe for further exploration and development in this vital sector.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.093 | 0.152 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".