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Record W4360859116 · doi:10.3390/en16072965

Energy Transition and the Economy: A Review Article

2023· review· en· W4360859116 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergies · 2023
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEnergy transitionRenewable energyEnergy securityFossil fuelSustainabilityEnvironmental impact of the energy industryBusinessEconomicsNatural resource economicsEnergy policyEngineering

Abstract

fetched live from OpenAlex

The global energy sector is in a period of transition, during which time it is expected that renewable and low-carbon energy sources, such as wind and solar, will replace traditional fossil fuels, including oil, gas, and coal. The energy transition is happening not only to limit the environmental impact of fossil fuel production and consumption but also to ensure energy security, reliability, access, affordability, and sustainability. The importance of the energy transition has been amplified by recent events, notably the Russian-Ukraine conflict. Economic, financial, and trade sanctions against Russia, and in particular its oil and gas industry, have forced countries to find new suppliers in the short term, but also to investigate new and more sustainable sources to guarantee long-term energy security. Given the importance of energy, it is perhaps not unexpected that there is a considerable body of recent academic literature, particularly over the last 4–5 years, studying what industries, consumers, governments, and markets can do to help bring about a faster energy transition. In this paper, we provide a review of the literature that pertains to the economic aspects of the energy transition. While our initial search of the literature is targeted at uncovering all relevant articles on the subject, we focus most of our discussion on the most influential articles in prominent journals and articles published in this journal—Energies. This review is intended to help identify active topics and potential research gaps and provide future direction, so we hope it will prove useful to the readers and authors interested in this topic.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.046
GPT teacher head0.258
Teacher spread0.212 · 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