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Record W2902937002 · doi:10.5555/1480-6800.21.1.43

The Adoption of Renewable Energy Policies in a Rentier State: A Case Study of the United Arab Emirates

2018· article· en· W2902937002 on OpenAlexvenueno aff
Hessa Murooshid

Bibliographic record

VenueArab world geographer · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyFossil fuelNatural resource economicsNatural resourceState (computer science)PoliticsEnergy securityOil reservesEnergy resourcesOil and natural gasNatural gasBusinessRenewable resourceEconomicsEconomyEnvironmental protectionEconomic policyEconomic systemPolitical scienceEnvironmental scienceEngineeringWaste managementPetroleum

Abstract

fetched live from OpenAlex

The United Arab Emirates (U.A.E.) represents a unique form of rentier state in the Gulf region, with its vast resources of oil and natural gas and its political and economic systems characterized by the exploitation and export of natural resources. The U.A.E. is a global leader in carbon dioxide emissions and pollution, but has recently begun to diversify its energy resources by establishing various renewable energy initiatives. This new strategy has involved new domestic policies that make important adjustments to the conventional fossil-fuel economic model. The main question addressed in this study is the following: What are the drivers that make a rentier state such as the U.A.E. adopt new policies to encourage alternative energy sources, given that its oil reserves are secured for almost the next 50 years? The study argues that current dynamics in the U.A.E. cannot be explained by rentier state theory but can be described as a post-rentierism moment, a phenomenon that did not emerge from a vacuum and ...

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
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 head0.020
GPT teacher head0.285
Teacher spread0.265 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2018
Admission routes1
Has abstractyes

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