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Record W2970380011 · doi:10.5539/jpl.v12n3p148

The Middle East Policy-Future Engagements of the U.S in Iran

2019· article· en· W2970380011 on OpenAlexvenueno aff
Abdulrahman Al-Fawwaz, Abdallah S. Abualkanam, Walid Khalid Abu-Dalbouh

Bibliographic record

VenueJournal of Politics and Law · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHalal products and consumer behavior
Canadian institutionsnot available
Fundersnot available
KeywordsMiddle EastUnrestForeign policyPoliticsTerrorismPolitical scienceLivelihoodPolitical economyDevelopment economicsEconomyGeographyLawSociologyEconomics

Abstract

fetched live from OpenAlex

The U.S is one of the foreign nations that have been deeply involved in the affairs of the Middle East region, particularly in Iran. The threat posed by terrorism to international peace and stability was one of the reasons why the U.S thought it wise to be involved in the affairs of the Middle East. Besides the insecurity concerns, laid the interests of the U.S in the region that is known to have vast reservoirs of oil and the leading producers of the source of energy in the world. According to the U.S, it would have been foolhardy to let the region slip into an era of political unrest as the rest of the world watched, yet the region is a source of livelihood and economies of different nations the world over because of their vast oil deposits. Consequently, the U.S drafted several measures and policies that, according to them, were aimed at restoring peace and political stability in the region. These included coalition building, supporting peace ventures, and provision of humanitarian aid. In their policies, they believed that a stable Middle East region would ensure a more stable world than was witnessed before their involvement. Despite their involvement in trying to find lasting peace in the region, the U.S has also encountered several challenges along their way that made their peace efforts slip every moment they thought they were close to finding lasting peace in the region.

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 score0.944
Threshold uncertainty score0.299

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 studies0.0000.000
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 head0.045
GPT teacher head0.304
Teacher spread0.259 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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