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Record W2621246924 · doi:10.5539/jpl.v10n3p83

The Prospect of the Relationship between the Islamic Republic of Iran and the Saudi Arabia: Plausible Scenarios

2017· article· en· W2621246924 on OpenAlexvenueno aff
Faisal M. Al- Shogairat, Vladimir Yurtaev

Bibliographic record

VenueJournal of Politics and Law · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMiddle East and Rwanda Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsMiddle EastPersianIslamIslamic republicPoliticsDevelopment economicsForeign policyCompetition (biology)Political scienceGeographyEconomyEconomicsLaw

Abstract

fetched live from OpenAlex

Islamic republic of Iran and Saudi Arabia are identified as two effective countries in sub-region of the Persian Gulf, that the radius of their influence covers whole great region of the Middle East. The relationship between the two countries have been full of tension during last decade, and during this period changes of political authorities of these countries were not able to improve this relationship. The cause is the resources of foreign policy behavior of the two countries, historical backgrounds of each country, as well as conflict of interest of each in the region of the Persian Gulf and the Middle East. The most competition atmosphere between the two countries is inside the three climacteric countries of Iraq, Syria and Yemen. Accordingly, the prospect of bilateral relations is a consequence of their behaviors in the region and also their dealings with these three countries. Three scenarios presented regarding the two countries' foreign policy in the region can be discussed: efforts to establish governments, attempts to maintain political structures of collapsing countries, and finally, continuation of current trends that may lead to disintegration of these climacteric countries. By studying these scenarios and drivers, blockers and their wild cards, this paper considers the second scenario best for both countries, which is consistent with their national interests, and with the region’s history and general situation.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.631
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
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 head0.054
GPT teacher head0.311
Teacher spread0.258 · 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.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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