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Record W2915035966

Economic Implications of Renewable Energy Transition in Nigeria

2018· article· en· W2915035966 on OpenAlexaff
Udoka C. Nwaneto, Udochukwu B. Akuru, Peter I. Udenze, Chukwuemeka C. Awah, Ogbonnaya I. Okoro

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSustenanceEnergy transitionRenewable energyElectricityNatural resource economicsEconomicsElectricity generationBusinessFossil fuelPower (physics)EngineeringPolitical science
DOInot available

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.680
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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.

Opus teacher head0.007
GPT teacher head0.206
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2018
Admission routes1
Has abstractyes

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