Interactions between proposed energy-mix scenarios and non-energy Sustainable Development Goals (SDGs): a Sub-Sahara African perspective
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Sub- Sahara Africa (SSA) has the lowest access to energy globally which is partly responsible for its dismal socio-economic indices. The continent, however, has the unique opportunity to fuel its sustainable development using clean and sustainable energy. Given the continent’s aspirations, as well as its position and peculiarities within the context of the Sustainable Development Goals (SDGs) such as its hosting up to 90% of the world’s poorest countries, and generally lagging behind in development as most countries in Africa are not on track to meet the SDGs with the exception of the SDG on climate action, an assessment of the interactions and implications between the goal to provide access to clean, reliable, affordable, sustainable, and modern energy (SDG 7) and the other non-energy related SDGs is important for coherent cross-sectoral sustainable development planning and decision-making. This paper analyzes the interactions between SDG 7 and selected non-energy SDGs for three energy-mix scenarios—the current (2018), 2040 energy mix scenario proposed by International Energy Agency (IEA), and 2065 energy mix scenario proposed by Joint Research Centre (JRC) of the European Commission. The analyses are done for two countries - Nigeria and Ethiopia—that capture the wide variation in economic growth and energy sources across SSA. The analyses were carried out by adapting a seven-point scoring typology proposed by Nilsson et al (2016). The results indicate that in the case of Nigeria, the interactions between SDG 7 and many non-energy SDGs, such as SDGs 2, 6, and 13, become negative for the IEA 2040 scenario while they were positive for 2018 scenario. For the same two scenarios (IEA 2040 and the current), for Ethiopia, there are some negative influences on selected non-energy SDGs, but the direction of overall interactions does not change from positive to negative. In the case of JRC 2065 scenario, there are marginal negative influences on some non-energy SDGs, but neither in Nigeria nor in Ethiopia, there is no complete reverse change from positive to negative for any non-energy SDGs. Hence, JRC 2065 scenario is preferred. The study concludes with recommendations for policy interventions that would prevent the change of the interactions that move from positive in the 2018 scenario towards negative in the 2065 scenario (such as those that protect the rights of local communities to natural resources), as well as policies that may reduce the influence of negative interactions seen in both scenarios (such as reduction of air pollution).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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