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Record W1923241039 · doi:10.7202/700963ar

La stabilité de l’OPEP

2005· article· en· W1923241039 on OpenAlexvenueno aff
The‐Hiep Nguyen

Bibliographic record

VenueÉtudes internationales · 2005
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsRivalryOligopolyPetroleumAgency (philosophy)Order (exchange)Stability (learning theory)EconomicsEnergy policyFunction (biology)BusinessIndustrial organizationEconomyMicroeconomicsComputer scienceEngineering

Abstract

fetched live from OpenAlex

In the energy field and more specifically in the petroleum sector, several models have been developed with a view to determining long-term price strategies and supply and demand flows without considering the sector in question from an oligopolistic perspective : institutions have been excluded from these models. This study explicitly recognizes the importance of variables often characterized as extra-economic and proposes to examine the degree of OPEC's stability. Among the factors that could negatively influence this stability are bilateral oil agreements, the coalition of consumer countries within the International Energy Agency and rivalry among the members of OPEC. The respective weight of each of these factors has been carefully examined. On the other hand, an oil price indexing formula accepted and respected by all parties concerned would ensure the stability of this organization. However, stability via indexing is unlikely as it is difficult to find a formula acceptable to all parties. It is therefore to be anticipated that the world energy and petroleum situation in the near future will be a function of the policies of the two poles : the United States, the largest consumer, and Saudi Arabia, the largest producer. The functions-objectives of these two countries have also been examined in order to derive a number of specific hypotheses relative to the eventual evolution of the energy and petroleum sector.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.981

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)0.0010.000

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 head0.015
GPT teacher head0.278
Teacher spread0.263 · 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 designNot applicable
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

Citations0
Published2005
Admission routes1
Has abstractyes

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