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Record W2865271585 · doi:10.22215/cjers.v8i1.2484

Has the Sovereign Wealth Fund of Azerbaijan (SOFAZ) Been Able to Promote Economic Diversification?

2013· article· en· W2865271585 on OpenAlexvenueno aff
Vahid Yücesoy

Bibliographic record

VenueThe Canadian Journal of European and Russian Studies · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsnot available
Fundersnot available
KeywordsSovereign wealth fundDiversification (marketing strategy)Dutch diseaseOil reservesRevenueEconomicsSovereigntyLanguage changeBusinessEconomic policyMarket economyEconomyFinanceExchange ratePetroleumPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Oil-rich countries have oftentimes been confronted with the challenge of diversifying their economies away from oil dependence given the exhaustible nature of these fossil fuels. Investing in sovereign wealth funds has been one of the most ubiquitous ways of preparing for the post-oil period. Investing in sovereign wealth funds rather than directly injecting the oil revenues in the economy not only precludes the outbreak of the Dutch Disease (which is known for giving rise to an exchange rate appreciation, crowding out non-oil industries and keeping the economy reliant on oil), but it also saves for future generations. Yet, in the case of Azerbaijan, the Sovereign Wealth Fund of Azerbaijan (SOFAZ), founded in 1999, has only increased this reliance on oil. Using the rentier states theoretical framework, this paper will argue that the direct control over SOFAZ exercised by the president and the lack of consultation with the NGOs have made corruption easier, making the task of economic diversification more difficult. This has been possible because through corruption the president has often resorted to oil money to buy peace rather than invest it in economic diversification. As a result, since the foundation of SOFAZ, the country is more reliant, not less, on oil.
 
 Full text available at: https://doi.org/10.22215/rera.v8i1.223

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.818
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.225
Teacher spread0.179 · 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 designTheoretical or conceptual
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

Citations1
Published2013
Admission routes1
Has abstractyes

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