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Record W1531618563 · doi:10.1080/15387216.2015.1057756

Geopolitics and revenue transparency in Turkmenistan and Azerbaijan

2015· article· en· W1531618563 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

VenueEurasian Geography and Economics · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsTransparency (behavior)GeopoliticsRevenueIncentiveEliteBusinessChampionEconomyMarket economyEconomic policyEconomicsPolitical scienceAccountingPolitics

Abstract

fetched live from OpenAlex

Azerbaijan and Turkmenistan, both rich in hydrocarbons, diverge in their attitudes toward global initiatives that promote transparency in extractive industries. While Azerbaijan became a champion of the Extractive Industries Transparency Initiative in the region, Turkmenistan declined to embrace the norm of revenue transparency. This paper analyzes the reasons for this outcome by evaluating the impact of external influences on the management of extractive industries in Turkmenistan and Azerbaijan since 1992. In particular, it questions the role of geopolitical and economic factors in making oil and gas revenues more transparent. The paper argues that in comparison with the leadership in Azerbaijan, the Turkmen elite had few incentives to cooperate with international organizations that promote transparency due to Turkmenistan’s dependency on Russian and Chinese pipelines and limited foreign investment from Western countries.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score0.974

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)0.0000.000

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 head0.028
GPT teacher head0.189
Teacher spread0.160 · 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